Lecturer Insights

Why digital ethics is important in modern organisations

"Digital ethics are critical to modern business organisations, guiding the responsible use of technology and ensuring transparency, fairness and accountability," says HSLU lecturer and AI ethics expert Dr Dimitrios Marinos. Adherence to ethical standards builds trust with stakeholders, fosters innovation and mitigates the risks associated with unethical behaviour, ultimately contributing to long-term success and sustainability.

Dr Dimitrios Marinos, our lecturer at HSLU, has deep expertise in artificial intelligence, big data analytics, digital transformation, AI ethics, data governance and more.

Digital ethics: A blocker or an opportunity?

In the modern era of digital transformation, the ethical considerations surrounding the use of technology within organisations have become increasingly important. Digital ethics encompasses a wide range of principles and practices that guide the responsible and ethical use of digital technologies. Within organisations, digital ethics presents both obstacles and opportunities that shape the way technology is developed, implemented and used.

Organisational blockers

One of the main blockers to digital ethics in modern organisations is the rapid pace of technological advancement. As organisations adopt cutting-edge technologies such as artificial intelligence, big data analytics and machine learning, they often face ethical dilemmas around privacy, transparency and accountability. The complexity of these technologies can sometimes obscure the potential ethical implications, leading to unintended consequences such as biased algorithms or unethical data practices.

Another obstacle is the lack of clear regulatory frameworks and guidelines for digital ethics. While some regulations, such as the General Data Protection Regulation (GDPR), provide guidelines for data privacy and protection, there is still a need for comprehensive regulations that address emerging ethical issues in technology. Without robust regulatory oversight, organisations may struggle to navigate the ethical landscape and ensure compliance with ethical standards.

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Organisational opportunities

Despite these barriers, digital ethics also presents significant opportunities for modern organisations. By prioritising ethical considerations in their use of technology, organisations can build trust with stakeholders, including customers, employees and regulators. Ethical practices such as transparent data collection and use, algorithmic fairness, and responsible use of AI can enhance an organisation’s reputation and mitigate the risks associated with unethical behaviour.

In addition, embracing digital ethics can foster innovation and creativity within organisations. By encouraging ethical thinking and decision-making among employees, organisations can harness diverse perspectives to develop technology solutions that prioritise social good and human well-being. Ethical considerations can also drive the development of sustainable business models that balance profit with social and environmental responsibility.

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Digital Ethics Framework

Although digital ethics is vital and every stakeholder needs to be covered, a very central question often arises: how do we study digital ethics?

Woven into every stage of technological innovation, ethical standards have a profound impact on society as a whole, shaping our global trajectory. As the pace of progress accelerates, so do the ethical challenges, requiring the continuous integration of new concepts and perspectives. The intricate interplay of complexity, nuance and rapid change makes it impossible for any one individual to claim mastery over every aspect of data and technology ethics.

The evolution of data ethics and responsible innovation standards and decision-making practices depends on collaboration, openness, curiosity, and an unwavering commitment to ongoing transformation. The Systemic Data Ethics Framework serves as a platform for collaboration and co-evolution. Rather than starting with an analysis of current practices and understandings, it takes a holistic approach, identifying twelve fixed domains, each of which represents an essential component necessary to realise the principles of data ethics.

Figure 1: Systemic Data Ethics Framework (Source)

This systemic structure provides stability while remaining flexible enough to accommodate new and diverse perspectives, even in an environment of constant change and innovation. This ability to absorb new insights is the foundation for managing the incredible complexity of the field, fostering cross-disciplinary and multicultural collaboration, encouraging inquiry and revealing interconnectedness. This model facilitates large-scale collaboration, creates new business opportunities and drives systemic change. Establishing a collaborative, systemic, human-centred approach as the default mode of engagement with data ethics is the critical starting point.

Digital ethics presents both obstacles and opportunities for modern organisations. While the rapid pace of technological advancement and lack of regulatory guidance present challenges, prioritising ethical considerations can build trust, foster innovation and create sustainable value for organisations and society as a whole. Embracing digital ethics is not only a moral imperative, but also a strategic one for organisations seeking to thrive in an increasingly digitised world.

We would like to thank Dr Dimitrios Marinos for his dedication and for sharing these valuable insights.

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Professional Data Science Portrait with Sarah Schneeberger: Research Associate, Lucerne University of Applied Sciences and Arts (HSLU)

Sarah Schneeberger is a passionate mathematician who wants to apply what she learned about data science during our Master's programme to bring us closer to the goal of a CO2-neutral world. In this interview, she tells us what she does in her current job as a research associate at Lucerne University of Applied Sciences and Arts (HSLU), what inspires her, and what activities tend to make her lose track of time.

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Sarah Schneeberger is a research associate at the Competence Centre for Thermal Energy Storage (CC TES), Lucerne University of Applied Sciences and Arts (HSLU) and a graduate of the Applied Information and Data Science Master’s programme @HSLU

First, please tell us a bit about yourself: Which hashtags describe you the best?

I would say #DataDeepDive #StayCurious #DataScienceForClimate #KnowledgeSharing.

Please tell us more.

For me, exploring the data, thinking about what it could mean, discovering the stories behind it, and coming up with solutions is like solving a complex puzzle, and I often lose track of time while doing so. I love analysing problems from different angles and learning and trying out new things. Data science is the epitome of continuous development because it combines the precise world of mathematics with the immense breadth of computer science. It’s vital for me to apply my skills so that I can work on something truly meaningful. I am passionate about contributing to the energy transition and finding ways to take us closer to a CO2-neutral world. I also believe that collaborating and sharing knowledge is the key to success and bringing about change.

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Let’s talk about your professional life: What do you do at HSLU?

I’m a research associate at the Competence Centre for Thermal Energy Storage (CC TES), which means I mainly work on projects. We work with clients from the manufacturing and service sectors to evaluate and develop thermal storage solutions for buildings, neighbourhoods and production centres. My tasks here are in the typical data science fields: collecting, interpreting and processing data; recognising patterns, and making and validating predictions. I also summarise, revise and communicate my findings, and of course I write reports and papers. It’s crucial for me to keep learning and stay current with the latest research. There are also opportunities to teach – for example, l’m about to teach an introductory math course. As we often work in small teams, we are also often busy managing projects.

What did you do before and why did you come to HSLU?

I studied maths at the University of Bern and worked for several years in IT at the Swiss Federal Railways (SBB). Initially, I coordinated projects, developed concepts and helped to get things up and running. During this time, I realised that I’d rather do the programming myself. This took me to the world of data science, where I saw an attractive career that combines my maths background with programming. The part-time programme at HSLU seemed like the ideal way to get me there. During my studies, I could transfer within SBB and work as a data engineer, which meant I could apply and deepen my knowledge of database construction and of data integration and processing. My Master’s thesis eventually led me to my current job, which involves a broad range of data science tasks.

Tell us about the most exciting part of your job.

I find it exciting to do research that provides a basis for making decisions and developing ways to contribute to a climate-neutral future. Collaborating with the various research institutes in Switzerland is very important and enriching. My job is also the ideal place to learn, meet challenges, and develop further. Being part of a diverse, inspiring and supportive team is very important to me.

What data science skills are most in demand in your work?

It’s crucial to have solid analytical skills and to accurately and efficiently analyse data. However, knowing about the different machine learning approaches and their advantages and disadvantages, not to mention being able to communicate and summarise the methods and results for clients, is more likely to give you a leg up in this type of work. Something that has attracted a lot of attention recently and will continue to do so is the use of generative artificial intelligence, such as ChatGPT.

Do you tend to see yourself as a techie, an analysis freak, a creative genius, a management superhero or a brilliant all-rounder?

The “analysis freak” label probably fits best.

What fascinated you the most about your studies (MSc in Applied Information and Data Science)?

The diversity of my fellow students really struck me. They came from different backgrounds and brought a vast range of perspectives and knowledge. I also found the hands-on nature of the courses to be very valuable. The fact that most lecturers also work outside the classroom ensures that the course is closely linked to the applied fields.

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What are the biggest challenges in your job at the moment?

Managing to keep an overview and getting everything done on time. I have a lot of creative freedom in my work, which is great, but it’s sometimes hard to stay focused and finish a project. It’s not always easy to know when you’re actually done with something – not just in my job but in data science in general. That’s because each step comes with a huge range of options you must consider – without losing sight of the deadline. So, you have to think carefully and make good choices to come up with a satisfying result.

How would you advise someone who wants to follow in your footsteps?

As I mentioned, it’s important to talk with your team members and ask for their advice. The key is to manage your time well and prioritise your tasks from the start.

And finally, what new hashtag are you aiming for?

Part of my degree involved organising and participating in a hackathon. I really enjoyed doing that, so I would like to participate in more hackathons in future, preferably with the same people.

We would like to thank Sarah Schneeberger for her dedication and for sharing these valuable insights.

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Lecturer Insights

Unlocking the key to effective organisational governance

Have you ever wondered why some organisations struggle to establish a robust governance framework? The latest article by our HSLU lecturer, Dr Dimitrios Marinos, reveals one critical factor: the integration of corporate values. Find out how integrating values into governance practices shapes ethical decision-making, fosters stakeholder trust and cultivates a culture of accountability.

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Dr Dimitrios Marinos, our lecturer at HSLU, has deep expertise in artificial intelligence, big data analytics, digital transformation, AI ethics, data governance and more.

Why corporate values play a crucial role

Corporate governance fails when it neglects to incorporate corporate values, because it undermines the ethical foundation that is essential for sustainable decision-making. Without the integration of guiding principles, governance mechanisms lack a moral compass, increasing the risk of ethical lapses, reputational damage and diminished stakeholder trust.

Corporate values play a crucial role in shaping an organisation’s governance framework and have a significant impact on its overall effectiveness. The impact of corporate values on governance is multifaceted and extends to various aspects of organisational behaviour, decision-making processes and stakeholder relationships.

Figure 1: Values are an essential part of the governance framework.

Corporate values have a profound influence on governance, guiding organisations through the complexities of decision-making. These values, deeply embedded in the fabric of an organisation, have a transformative effect on governance practices. This essay explores the multifaceted impact of corporate values on governance, unravelling how shared principles shape ethical decision-making, stakeholder relationships and overall organisational sustainability.

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Ethics, transpareny and integrity

At the heart of corporate values is an unwavering commitment to ethical behaviour, transparency and integrity. Aligning governance with these values empowers it to provide a robust framework for ethical decision-making, guiding organizations towards principled decisions. Ethical decision-making, underpinned by corporate values, becomes the linchpin of effective governance, fostering a culture of trust and accountability.

Aligning governance with corporate values lays the foundation for building trust between organisations and their stakeholders. Whether they’re customers, employees, investors or the wider community, stakeholders value authenticity and integrity. Governance practices that reflect an organisation’s values cultivate and sustain trust, thereby fostering a positive reputation. Trust acts as a currency that pays dividends in the form of loyalty, positive word-of-mouth and enduring stakeholder relationships.

Figure 2: The layers of impact on shareholder value.

The values shape an organization’s culture. When leadership reflects these values, they permeate the workplace and shape the behaviour of employees and leaders. A strong organisational culture based on shared values creates a sense of purpose and unity. When aligned with these values, governance transcends rules and regulations to shape a positive and ethical working environment as a guiding force.

Corporate values provide a benchmark against which to measure leadership accountability. Values-based governance holds leaders accountable for upholding ethical standards and staying true to the organisation’s mission. This accountability helps prevent leadership misconduct by ensuring that leaders embody transparency, accountability and responsible stewardship. Governance practices rooted in the company’s values create a culture synonymous with leadership integrity.

Sustainability, which encompasses the enduring success of an organisation, becomes a key consideration, guided by corporate values. Governance practices influenced by these values prioritise long-term sustainability over immediate gain. This perspective encourages strategic decision-making that considers the impact on stakeholders, the environment and society at large.

Values-based governance is forward-looking and contributes to organisational resilience and sustainable success. The impact of corporate values on employee engagement and retention is significant. Experiencing governance structures aligned with the organization’s values fosters pride and commitment among employees. Values-based leadership fosters a positive workplace culture that acts as a magnet for talent acquisition and retention. Employees become active participants in a shared journey guided by common values.

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Corporate values often include a commitment to social and environmental responsibility. Values-driven governance practices translate into responsible business conduct, ethical sourcing and sustainable practices. Values-based governance goes beyond the profit motive to consider the broader societal impact. This commitment enhances the organisation’s reputation and positions it as a positive force for social good.

Values have a transformative influence on governance, shaping the ethical climate, stakeholder relationships and overall sustainability of the organisation. Integrating values into governance structures and decision-making processes becomes the bedrock of responsible and principled leadership.

The lasting success of an organisation depends not only on financial acumen, but also on a values-driven approach to governance that makes a positive contribution to the world. Corporate values are no longer just words on paper; they become the cornerstones that support the pillars of ethical leadership and sustainable business practices.

We would like to thank Dr Dimitrios Marinos for his dedication in sharing these wonderful insights with us.

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The Impact of Low Governance on Modern Leadership

Today, many organisations and leaders aspire to great leadership. But is it only skills that contribute to great leadership? Data science without substantive governance can be a fatal tool in today's organisational landscape, taking leadership and decision-making to a different level. Our HSLU lecturer, Dr Dimitrios Marinos, provides helpful insights into how a strong governance framework could help solve leadership mishaps now and in the future.

Dr Dimitrios Marinos, our lecturer at HSLU with expertise in artificial intelligence, big data analytics, digital transformation, AI ethics, data governance and more.

Why successful organisations need a strong governance framework

Given the current market and societal needs in today’s labour market, leadership is central to retaining talented employees, generating healthy growth and ultimately creating (shareholder) value. Universities and institutes around the world are now offering masters degrees and various types of studies to enhance the leadership skills of employees and senior managers. But is it only about leadership skills? What if the organisation does not provide the right environment, based on a strong governance framework, to be an empathic leader?

Leadership is profoundly influenced by governance, creating a symbiotic relationship that shapes organisational culture, decision-making processes and overall effectiveness. Governance provides the framework within which leaders operate, offering policies, structures and principles that guide their actions and decisions.

The influence of governance on leadership is multi-faceted. First and foremost, governance sets the parameters for ethical behaviour and responsible leadership. It sets expectations for transparency, accountability and compliance with legal and regulatory standards. Leaders, in turn, are charged with upholding and embodying these principles and serving as role models for the entire organisation.

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The Enron and Tyco International scandals – how not to lead

In examining real-world cases, the Enron scandal serves as a stark illustration of how governance failures can facilitate unethical leadership behaviour. What happened? Enron’s leadership took advantage of weak oversight and inadequate checks and balances to engage in fraudulent financial practices that ultimately led to the company’s collapse. This governance vacuum allowed executives to prioritise short-term gains over ethical considerations, with serious consequences for employees and investors.

Similarly, the Tyco International scandal involving executives Dennis Kozlowski and Mark Swartz highlights the impact of poor governance on leadership behaviour. The lack of proper controls enabled the executives to commit corporate fraud and embezzlement, demonstrating how governance failures can embolden executives to act against the best interests of the organisation and its stakeholders.

How Johnson & Johnson overcame a crisis

In contrast, the Johnson & Johnson Tylenol crisis demonstrates the positive synergy between effective governance and responsible leadership. Faced with a product tampering crisis, Johnson & Johnson’s leadership responded quickly and decisively by recalling the product and implementing safety measures. This incident highlights how robust governance structures, including crisis management frameworks, empower leadership to make ethical decisions and prioritise consumer safety. In essence, these real-life scenarios highlight the central role of governance in shaping leadership behaviour and organisational outcomes.

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Why a governance framework is a win-win for modern organisations

In addition, governance structures define the distribution of power and decision-making authority within an organisation. Leaders operate within these structures, whether hierarchical or decentralised, which significantly affects their ability to implement change, make strategic decisions and foster innovation. Effective governance aligns leadership actions with organisational goals, ensuring a coherent and focused approach to achieving objectives.

Moreover, governance mechanisms often include checks and balances to mitigate risk and prevent abuse of power. These safeguards provide assurance to stakeholders, including employees, customers and investors, and foster trust in leadership. Conversely, poor governance can lead to leadership failures, ethical lapses and a breakdown in stakeholder trust.

Below we have outlined six pillars that would actually improve leadership through governance. These six principles range from communication to shareholder engagement, increased transparency and a more inclusive approach to operations. Major US companies have already recognised the benefits of these pillars, as they have seen improvements in employee satisfaction and a more thriving working environment.

Figure 1: The exit plan on the basis of six pillars that would actually improve leadership through governance.

1. A strong governance framework

Establish a robust governance framework that is aligned with the organisation’s mission, values and long-term goals. Ensure that governance structures are well defined, adaptable and reflect best practice.

2. Leadership development and training

Invest in leadership development programmes that emphasise ethical decision-making, effective communication and strategic thinking. Provide ongoing training for leaders to enhance their governance awareness and skills.

3. Transparent communication

Promote transparent communication between management and stakeholders. Clear, open and honest communication builds trust and ensures that stakeholders are well informed about the organisation’s decisions and actions.

4. Diversity and inclusion

Integrate diversity and inclusion principles into governance structures. Diverse perspectives at the leadership level contribute to more inclusive decision-making and reduce the risk of bias.

5. Stakeholder engagement

Actively engage with stakeholders to understand their expectations and concerns. A governance approach that incorporates stakeholder input ensures that management decisions take into account the wider impact on the organisation.

6. Continuous improvement

Embrace a culture of continuous improvement in both governance and leadership. Regularly reassess governance practices and leadership effectiveness, adapting to changing circumstances and organisational needs.

By proactively addressing these considerations, organisations can create a positive synergy between governance and leadership, ensuring that governance structures support rather than hinder effective and ethical leadership practices.

So how does your organisation improve leadership through governance?

We would like to thank Dr Dimitrios Marinos for his dedication in sharing these wonderful insights with us.

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Data Science Research and Project Portrait

When Zurich Becomes A Sponge City – A Data Science Research Project by Sascha Kappeler

Climate extremes such as droughts, heat waves and heavy rainfall are becoming more frequent and are affecting even large cities such as Zurich. In response, research institutions such as the Zurich University of Applied Sciences (ZHAW) are developing "sponge cities". Sascha Kappeler, a graduate of HSLU's Master of Applied Information and Data Science, analysed data from the Giessereistrasse pilot project for his thesis. Discover the benefits of sponge cities and how data-driven insights can guide urban areas in building sustainable and resilient green infrastructure to adapt to extreme weather events.

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Sascha Kappeler, Applied Information and Data Science Masterabsolvent, Hochschule Luzern

Sascha Kappeler, our former Applied Information and Data Science Master’s student at HSLU (graduate since 2023).
Data, Analytics and AI Engineer at cablex AG.

First of all, tell us something about yourself: What hashtags best describe you?

#AnalyticThinker
#DataDriven
#LeanMindset

Tell us more about the hashtags.

The chosen hashtags characterise not only my professional but also my personal personality.

#AnalyticThinker represents my way of thinking. For me, an analytical approach is the key to solving challenging problems and coming up with innovative ideas.

#LeanMindset is my belief that less is often more. This mindset drives me to constantly look for ways to optimise processes. It underpins the way I work. Getting the best out of every situation is my approach.

#DataDriven stands for my constant curiosity and determination to gain knowledge and insight from data. Even in my private life, I prefer to have a statistical analysis for everything.

About your job: What do you do at cablex AG?

I currently work as a Data, Analytics & AI Engineer at cablex AG. Overall, this job is very versatile. It covers the entire data processing process, from raw data management to the design of user-friendly dashboards. During my studies at cablex AG, I had the opportunity to put my knowledge into practice. For example, I worked on setting up a data warehouse (DWH) from the very beginning. One of my daily tasks is the ongoing maintenance of the DWH. The DWH contains data from various sources. I work on developing appropriate data models to define the structure and relationships of the data. These models form the basis for creating meaningful dashboards. I work closely with the business units to provide tailored insights into relevant data and metrics. These help the teams in their day-to-day work to gain profitable insights and make data-driven decisions.

What did you do before and why did you join cablex AG?

My career began with an apprenticeship as a chemical laboratory technician. I then successfully completed a bachelor’s degree in biotechnology, specialising in pharmaceutical technology. In the following years, I gained a lot of experience in the development of cosmetic products. After that, I decided to do a Masters in Data Science to get a foothold in the field. I was therefore delighted to quickly find a suitable position in the field of my studies. Here, I was able to apply the knowledge I had acquired directly in a professional context. The job and activities at cablex AG offered the perfect opportunity to do this. At the same time, it was a steep learning curve.

The Project

Tell us about your research project.

Instead of relying on a grey infrastructure of levees, pipes, dams and canals, sponge cities allow urban areas to absorb water during heavy rainfall and release it during droughts (Qi et al., 2020). As the risk of flooding increases with climate change, we need to design cities like giant sponges. This system allows water to drain away safely (FOEN/ARE, 2022). The aim of a sponge city is therefore to reduce flooding, water pollution and water scarcity in urban areas. Furthermore, sponge cities have the aim of replacing or reducing many energy-intensive water treatment systems in cities (Kruse, 2015).

Here are some impressions of how the Sponge City element works:

Thanks to the special design, rainwater is directed directly into the vegetation zone, where it is stored in the ground. Only in the winter months is the water discharged into the sewer system due to the use of de-icing salt (Source: ZHAW/IUNR, 2021).

Carefully placed trees with urban suitability complete the sponge city element. Sensors continuously collect data on weather conditions, soil properties and sap flow. Selected vegetation provides shade and promotes biodiversity (Source: ZHAW/IUNR, 2022).

View of a section of the Sponge City from another perspective. The focus is on three of the nine trees planted as part of the research and associated data analysis (Source: ZHAW/IUNR, 2023).

The figure visualises 27 soil sensors in 3D, coloured according to soil depth. In the master’s thesis, they were grouped using k-means clustering and coloured accordingly to show and evaluate the spatial distribution of the clusters.

The Zurich University of Applied Sciences (ZHAW) in collaboration with the Institute for Environment and Natural Resources (IUNR), redesigned a section of Giessereistrasse in Zurich to align with the Sponge City 2020 concept. The pilot project involved measuring various climate and soil data on site. It also monitored the sap flow of the planted trees.

The Master’s thesis aimed to extract maximum insights from the collected data for the constructed Sponge City element through appropriate data analyses. Thanks to contact with the leading expert in Switzerland’s Sponge City field, Stefan Stevanovic of the Plant Utilisation Research Group, I successfully completed my Master’s thesis. His crucial expertise and support enabled me to blend my scientific background with newly acquired knowledge in data science.

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Results and Findings

What data and method did you use, and what insights did you gain or hope to gain?

I used data from various monitoring stations in “Schwammstadt” (Sponge City) which the ZHAW has provided me. They installed soil sensors to measure volumetric soil moisture and soil temperature. Additionally, they established multiple stations to collect comprehensive climate data from the surrounding area, including air temperature, precipitation, and global radiation levels.

In addition, sap flow sensors on the trees measure the amount and direction of sap flow (= water flowing up the tree). Sap flow in trees is an important indicator of their health and well-being. It provides important information about the physiological activity and metabolism of trees. An efficient and stable sap flow indicates that the tree is in a healthy condition. Conversely, a disrupted sap flow can indicate stress factors such as drought, disease or pests.

I used the XGBoost machine learning method to generate sap flow predictions using existing climate and soil data. These predictions can help identify stress factors in the trees, which can help maintain their health. It enables more efficient use of resources, for example by adapting irrigation systems to the specific needs of trees, resulting in water and energy savings. The results, which combine climate data with SAP flow predictions using machine learning and feature importance analysis, provide a new perspective for studying the interactions between environmental factors and trees.

In addition, the application of the k-mean clustering method to the soil sensors enabled a better understanding of the responses of the soil to environmental influences such as rain events and external temperature variations. As well as providing valuable insights into the responses of the soil sensors to external environmental influences, this approach also highlighted the important role of the structural design of a sponge city. This includes aspects such as the slope of the ground, the impact of road infrastructure and the distribution of vegetation, all of which have a significant impact on the performance of the sponge city. These findings provide an opportunity to optimise the construction and design of future sponge cities, making urban living spaces more efficient.

How can your insights help our society?

Overall, the data analysis of sponge cities will help our society to design sustainable and resilient cities. The threat of climate change requires cities to better adapt to extreme weather events. Data analysis of sponge cities provides valuable insights into how to deal with challenges such as heavy rainfall and heat waves. By understanding how sponge cities efficiently absorb and store rainwater, cities can become more resilient to extreme weather events. This will allow cities to better prepare for these events and minimise the impact on the population. In addition, the data analysis I conducted revealed several factors influencing the design of a sponge city that we can take advantage of.

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How would you like to pursue your project in the future?

Having successfully submitted my Master’s thesis and completed my active involvement in the project, I am now very interested in keeping up to date with developments. I am curious to see how my research findings will have an impact in practice. The findings from the Master’s thesis have already supported the research team in other projects.

Although I am no longer actively involved in the project, I maintain close contact with the ZHAW, which commissioned the thesis. This allows me to keep abreast of developments and the potential impact of my findings. This connection allows me to offer support and valuable insights at any time. I am sincerely grateful for the opportunity to work on this project and look forward to further research and the positive changes it can bring about in the future.

How did your studies influence the project?

The HSLU is open to motivated and interested students in this degree programme, thus enabling career changers like me to continue their education in this field. Despite my lack of programming skills, I was able to start the Master’s programme and acquire a broad knowledge in various areas of data science during my studies. The interdisciplinary insights into the world of data analysis enabled me to select and successfully apply appropriate evaluation and visualisation methods in my Master’s thesis in order to efficiently answer my research questions.

What advice would you give to others starting similar projects?

The advice I would give to future students are basic principles that many already know. The real challenge is to put these principles into practice. A solid foundation for a successful thesis starts with a thorough literature review. Existing scientific papers provide an opportunity to learn from them and enrich them with your own ideas and extensions. To avoid time-consuming revisions, it is advisable to start early with a careful examination of the data and its quality. I also recommend that you seek ongoing feedback from your supervisor or client, rather than handing in your work at the end. This will ensure that the work meets expectations and provides the client with the greatest possible benefit.

And now for the end: What new hashtag are you aiming for in the future?

I’m aiming for the #TimeforMe hashtag for 2024. This hashtag stands for my plans to pay more attention to my time and personal needs in this year. Writing my Master’s thesis while working full-time has been the main focus of 2023. This required a lot of commitment and sacrifice, including many hours of weekend work. I faced a steep learning curve in both my Master’s thesis and my day-to-day work, and placed the highest value on quality in order to achieve excellent results. In this year, my main focus will be to find a balance between professional commitment and personal care by taking time for rest and personal growth.

We would like to thank Sascha Kappeler for his dedication in sharing this wonderful portrait of his research project with us.

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Data Science Research and Project Portrait

Automated Topic and Trend Detection in Customer Comments Using NLP

Dominik Finzer's dream of becoming a data scientist did not begin as a child. But life had other plans. Now he works with thousands of written comments every day in the Customer Insights and Analytics department at SBB. In our interview, he talks about his master's thesis, the results of which did not end up in a drawer, but added real value to the wishes and needs of the people who travel with the Swiss Federal Railways. Find out how Dominik uses his Applied Data Science skills to measure customer satisfaction.

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Dominik Finzer, our former Applied Information and Data Science Master’s student at HSLU (Graduate since 2023)
Data Scientist in the Customer Experience & Analytics department @SBB CFF FFS

First of all, tell us something about yourself: What hashtags best describe you?

#StayCurious
#LifeLongLearning
#WhySoSerious?

Tell us more about the hashtags.

Since I was four years old, my dream has been to become a data scientist (end of irony).
To find out if something is for me, I have to try it. As a child, I didn’t know which career was right for me, so I tried a lot of things. Looking back, I have never regretted trying new things and moving on when the time was right. Each job has taught me something and given me something that I wouldn’t want to have missed. Staying curious, getting to know new people and problems, and getting out of my comfort zone has helped me personally to find joy in my work and in my free time. Last but not least, don’t take yourself too seriously. Humour is also very important to me, very important in everyday working life. If you can laugh together, you can face challenges together.

What do you do at SBB?

I currently work as a data scientist in the Customer Experience & Insights department. I work in an interdisciplinary team of data scientists, statisticians, designers and psychologists. Our goal is to bring the customer’s perspective into the company and help to ensure that the wishes and needs of customers are more strongly integrated into decisions and the related services. In my role, I am primarily responsible for providing this customer perspective in the form of data and analysis. In addition to linking data from various customer satisfaction measurements with other company data, a key task is to record relevant questions from the company. With the data available and the issues identified, I help to create a reliable basis for making more customer-centric decisions.

What did you do before and why did you join SBB?

After a basic technical apprenticeship in the automotive industry, I studied industrial engineering. I then worked as a business analyst and project manager, first at a start-up in Basel and then at an IT consulting firm in Bern. I’ve been with SBB since 2018, where I first worked as a corporate architect. In this role, I learnt that complex issues can be communicated much better with well-designed visualisations. To improve my skills in this area, I undertook further training in data visualisation and met a designer along the way. Together, we decided to take on the position of “Project Manager Data Visualisation and Storytelling” in 2021 as part of a job share. At the same time, I started my Master’s degree at HSLU to deepen my knowledge in the field of data science and, in particular, to improve my programming and engineering skills.

The Project

Tell us about your research project.

When measuring customer satisfaction at SBB, in addition to the structured data that comes from customer ratings, we collect a lot of free text comments in which customers express additional concerns. The effort required to write such a comment always costs respondents time. So the hypothesis was that these comments contain issues that are particularly emotional for customers. As these comments are still only read sporadically, the idea was to use today’s natural language processing (NLP) methods to mine this “treasure trove” of data and gain new insights into customer concerns.

*For an interactive graphic, please click on the image*.
Topic clusters meet keywords: The graph shows the themes extracted from the comments and the keywords behind them to illustrate which aspects move customers emotionally.

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Result & Findings

What data did you use, what method did you apply, and what key insights did you gain or hope to gain from it?

Between 2018 and 2022, more than 60,000 customer comments were written, which served as the basis for this work. As these comments were not categorised in advance, the main objective was to automatically identify the topics and assess their relevance to customers. To do this, I used topic modelling, a form of unsupervised machine learning, to extract patterns and key themes from large collections of text data. The insights gained enabled a deeper understanding of customer opinions and needs. Of particular note was the ability to combine these results with available structural data such as age, gender, timing and purpose of travel to gain deeper insights into different customer groups.

Topic Modeling helps to extract patterns and key themes from large collections of text data. The insights provide a deeper understanding of customer opinions and needs.

How can your insights help our society?

Topic modelling offers the potential to process information more efficiently by automatically recognising patterns in large textual data. This allows people to focus on their strengths, such as creative thinking, collaboration and strategic decision making, rather than spending valuable time on manual data processing. At a societal level, this helps to free up resources for innovation-enhancing activities and social collaboration, ultimately contributing to a more advanced and efficient society.

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How would you like to pursue your project in the future?

The Master’s thesis focused on a limited data set to demonstrate the possibilities and limitations of the method. The aim now is to transfer the developed approaches to operations. Specifically, new customer feedback will be analysed on a daily basis. The aim is to identify trends and new customer concerns more quickly and to develop appropriate measures, always with the aim of strengthening customer orientation.

How did your studies influence the project?

My studies have had a crucial influence on this project. Without the skills I acquired during my studies, I would not have been able to carry out this work. The modules of the MSc Applied Information and Data Science not only taught me basic skills such as programming in Python or working with databases, but above all showed me how to deal efficiently with different challenges. Looking back, the MSc was perfect for filling my knowledge gaps, especially in the technical area, and preparing me for a career as a data scientist.

What advice would you give to others starting similar projects?

Try to get access to the data you need as early as possible and focus on a clear research question. Allow plenty of time for data preparation, often much more than you think. I was particularly fortunate to be accompanied by an expert who provided very valuable technical and methodological input and took the time to scrutinise my interim results. With the support of a professional contact person in the company who understands the challenges, the Master’s thesis can become something that doesn’t disappear into a drawer, but brings real added value to you and the company.

And now for the end: What new hashtag are you aiming for in the future (e.g. for next year)?

It will stay the same next year, but with a bit more free time for other hobbies and projects :).

#StayCurious
#LifeLongLearning
#WhySoSerious?

We would like to thank Dominik Finzer for his dedication and time in sharing this wonderful research project portrait with us.

Programme Info: MSc in Applied Information and Data Science
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Data Scientist Professional Portrait

Professional Data Science portrait with Kail Kuhn: Co-Founder and Lead Data Scientist at Syntera GmbH

Curious, adventurous, active and intense: That's how Kail Kuhn describes himself. He is Co-Founder of Syntera GmbH and Lead Data Scientist of this innovative start-up company based in Lucerne. Before embarking on his entrepreneurial career, he completed our MSc in Applied Information and Data Science at HSLU. In our interview, he talks about his love of digging deep into data, wearing multiple hats, and the adventurous spirit leading him to visit his family in Chile.

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Kail Kuhn, HSLU Master's graduate in Applied Information and Data Science

Kail Kuhn
Co-Founder and Lead Data Scientist @Syntera GmbH
Applied Information and Data Science Master’s graduate @HSLU

First of all, tell us something about yourself: What hashtags best describe you?

#Curious #Adventurous #Active #Intense

Tell us more about them:

#Curious: I have an innate eagerness to learn new things, both in my personal and professional life. I enjoy talking to people from different walks of life to understand their perspectives and visions. This curiosity extends to being open to new experiences and challenges that come my way.

#Adventurous: I’ve never taken the easy way out, especially when it comes to pursuing my interests and passions. Whether it’s making big life decisions or travelling to different parts of the world, my adventurous spirit has always guided me. It’s about embracing the unknown and learning from different cultures.

#Active: My life is a whirlwind of activity. Between my demanding role at Syntera and my personal life, which includes annual trips to Chile to visit my family, there’s never a dull moment. It keeps me on my toes and makes every day exciting.

#Intense: I’m passionate about what I do and who I am. This intensity manifests itself in my work ethic, my hobbies and my relationships. It’s what drives me to excel and gives my life a sense of purpose.

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Now let’s talk about your professional life: What do you do at Syntera GmbH?

I’m the Co-Founder and Lead Data Scientist at Syntera GmbH, a startup based in Lucerne, Switzerland. We focus on helping companies unlock the potential of their data. My role is multifaceted: in addition to designing, developing and implementing analytics solutions using cloud technology and big data tools, I also spend time looking for new business opportunities to further grow our company. At the moment, one of the most interesting parts of my job is talking to other like-minded people, understanding their business vision and developing a plan to help them achieve their goals in the most efficient way using technology.

What have you done before and why did you join Syntera GmbH?

Before co-founding Syntera GmbH, I worked as a consultant at Saracus Consulting AG, where I maintained a complex DWH environment for the State Secretariat for Economic Affairs in Bern. Before that, I was a Data Scientist at Westphalia DataLab, where I gained my first experience in a data science start-up in Münster, Germany. So why did I decide to join Syntera? The answer lies in the alignment of my passion for data science with the entrepreneurial spirit. I saw an opportunity to make an impact on a larger scale and be involved in every aspect of the business, and I had the perfect partners in Dimitri Bütikofer and Dominic Schranz to realise this vision. Together we want to revolutionise the way companies use data and I couldn’t be more excited about this journey.

Tell us about the most exciting part of your job.

The most exciting aspect of my job is undoubtedly the community we are part of. We are proud alumni of the Lucerne University of Applied Sciences and Arts and our company is based in the university’s Smart-Up hub. This gives us an academic touch and a nurturing environment for innovation. We also make it a point to regularly attend Microsoft events, as we use Microsoft technology extensively to help our customers. But what excites me most is our membership of the LAC2 community in Lucerne. This community acts as a melting pot for all players in the AI ecosystem in Central Switzerland. It provides a fantastic opportunity to connect, learn and collaborate, which enriches our work at Syntera GmbH.

What Data Science skills are most in demand in your role?

While you might think that hard skills like programming and machine learning algorithms are the primary requirements for a data scientist, I’ve found that soft skills like communication and project management are just as important. Effective communication is key to translating complex data insights into actionable business strategies. Project management skills help to structure work and ensure efficient use of time and resources. Both skills are essential in a start-up environment where you’re expected to be a jack of all trades.

Do you see yourself as a technician or an analyst? Or a creative genius, management superhero or generalist wizard?

I would describe myself as a cross between an ‘analysis freak’ and a ‘creative genius’. I love digging deep into data to uncover insights, but what really energises me is the creative process that follows the analysis. Whether it’s designing a new experiment to test a hypothesis or crafting a compelling data story, the creative aspect makes the analytical work even more rewarding.

What do you remember most about your time on the MSc in Applied Information and Data Science?

During my MSc in Applied Information and Data Science at HSLU, what struck me most was the diversity of the student body. Almost all were working professionals from different industries, and the one thing that united us was our shared passion for data science. In terms of coursework, the development of my Master’s thesis was a highlight. It provided a comprehensive platform to apply everything I had learned. The diversity of perspectives enriched my learning experience, while the thesis work gave me a satisfying sense of accomplishment.

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What are the biggest challenges in your job at the moment?

The dynamic nature of a startup brings its own set of challenges, the most pressing of which is wearing multiple hats. One moment I am immersed in data analytics, the next I am in a client meeting explaining our services. Balancing these different roles, especially the shift from a technical to a sales mindset, is challenging but also exhilarating. It pushes me to constantly adapt and grow.

What advice would you give to others starting out in the same role?

The best advice I can give is to be passionately curious. Look for things that pique your interest and align them with your professional goals. Keep learning, not just from courses or books, but also from the people around you. And above all, enjoy the journey. If you’re passionate and curious, you’re already on the road to success.

And finally: What new hashtag are you aiming for?

#Focused. 2023 has been quite rewarding so far, both professionally and personally. My goal for the remainder of the year is to maintain this momentum. Staying focused will be critical to capitalising on the various opportunities I expect to be presented to me.

We thank Kail Kuhn for his dedication and time to share these valuable insights with us.

Programme Info: MSc in Applied Information and Data Science
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Data Scientist Professional Portrait

Professional Data Science portrait with Daniel Barco: PhD student

For Daniel Barco, our MSc in Applied Information and Data Science graduate at HSLU, the mission is crystal clear: to use his data science skills to improve people's lives through AI technologies. Find out how the PhD student fights malaria and cancer on a daily basis.

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Daniel Barco
PhD student @Centre for Artificial Intelligence (CAI) at the Zurich University of Applied Sciences (ZHAW)
Applied Information and Data Science Master’s graduate @HSLU

First of all, tell us something about yourself: What hashtags best describe you?

#DataScienceForSocialGoods #DetectMalariaAI #AI4RadiationTherapy

Tell us more about them:

These hashtags suit me very well! #AI4RadiationTherapy is for my work in radiotherapy as part of my PhD, and #DetectMalariaAI is for my malaria detection project.

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Now let’s talk about your professional life: What do you do at the Centre for Artificial Intelligence (CAI) at the Zurich University of Applied Sciences (ZHAW)?

At CAI, I am working on an exciting project where we are developing new AI algorithms to improve radiotherapy. We are working closely with our implementation partner to create high-quality 3D models of the body and tumours from just a few 2D CT images. Our goal is to reduce radiation exposure for cancer patients.

What have you done before and why did you join the CAI?

I used to work as a data scientist and part-time on a project to develop AI-based malaria detection software. This software uses microscopic images to help lab technicians in malaria-endemic areas detect malaria faster and more accurately. The software was successfully tested in Angola and has been used in a local hospital since the beginning of the year.

Tell us about the most exciting part of your job.

The most exciting thing about my job is that I can help improve people’s lives through the use of AI technologies. That’s really fulfilling!

What Data Science skills are most in demand in your role?

In my job, deep learning skills are in high demand, especially in medical imaging. I use Python and PyTorch (PyTorch Lightning) on a daily basis. It also involves reading and understanding publications by other scientists.

Do you see yourself as a technician or an analyst? Or a creative genius, management superhero or generalist wizard?

At the moment I would describe myself as more of a techie, because I spend a lot of time writing software.

What do you remember most about your time on the MSc in Applied Information and Data Science?

I am fascinated by the craft of data science. By craft, I mean programming, setting up data pipelines, building and tweaking models, and understanding solutions that have already been developed. Now I have the opportunity to use this craft to make a positive difference in global development.

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What are the biggest challenges in your job at the moment?

One of my biggest challenges is finding the time to work on the malaria project. Besides my PhD, there is sometimes not as much time as I would like to spend on the project. We are currently in talks with the Italian Institute of Tropical Medicine to label our images from Angola. I hope to find enough time during my PhD to continue this project. For more information, please visit www.malariadetection.ch.

What advice would you give to others starting out in the same role?

There are many ways to do good with AI systems. For me, it was a great motivation to consciously focus on data science for social good and learn new skills.

And finally: What new hashtag are you aiming for?

#GetFunding4MalariaDetection #AI4SocialImpact

We thank Daniel Barco for his dedication and time to share these valuable insights with us.

Programme Info: MSc in Applied Information and Data Science
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Professional Data Science portrait with Irma Glatt: BI Consultant/Data Analyst

"I couldn't imagine how much fun a functional piece of code could be," says Irma Glatt, our Master's graduate in Applied Information and Data Science at HSLU. Coding in Python and R made a big impression on her. From that day on, she understood the great potential hidden in data. Now she works with it every day as a BI Consultant and Data Analyst at Bison Schweiz AG. Dive into Irma's fantastic world of digits, data and code.

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HSLU Applied Information and Data Science graduate Irma Glatt

Irma Glatt
BI Consultant/Data Analyst @Bison Schweiz AG and
Applied Information and Data Science Master’s graduate @HSLU

First of all, tell us something about yourself: What hashtags best describe you?

#continouslearning, #changeperspectives, #analytics, #bigpicture, #detailsmatter, #variety

Tell us more about them:

I am a person who likes to analyse things – be it business data at work, a group travelling by train, or the latest Netflix movie. I enjoy questioning things, looking at them from different angles and levels of detail, and then learning from what I found. That’s probably why I like further education so much. I’m definitely no fan of routine work.

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Now let’s talk about your professional life: What do you do at Bison?

I joined Bison in June 2022 as a BI Consultant/Data Analyst. In this role, I can support our customers in developing their data strategy while doing the requirements engineering with them for BI projects, which I then also manage. At the same time, my job requires me to visualize the necessary data and analyses with the help of a business intelligence tool.

What have you done before and why did you join Bison?

Previously, I worked as an IT project manager and requirements engineer for a small IT company that develops customized software. While working there I learned more and more about databases and thus discovered how much I enjoyed working with data. After completing the Applied Information and Data Science Master’s programme, I decided to look for a job with an even stronger focus on data.

Tell us about the most exciting part of your job.

Besides us data analysts, we also have data engineers and scientists in our BI team, although the task boundaries are pretty loosely defined, despite our official roles. This allows us often to work outside our formally defined function and is what makes the work so varied and exciting.

What Data Science skills are most in demand in your role?

It is very useful to understand the potential hidden in data – for example, by asking yourself how to extract the right information from it and thus add value for the customer. Good analytical skills are also key to understanding complex relationships within data. And you need to have good technical skills, for example in working with databases and BI tools.

Do you see yourself as a technician or an analyst? Or a creative genius, management superhero or generalist wizard?

I find it exciting to track down a flawed data set across multiple systems or to spend the day checking the code of a complex SQL query. But I also enjoy having contact with clients and working on strategic challenges. I like to see the details as well as the big picture. Therefore, the “generalist wiz” label probably fits best.

What do you remember most about your time on the MSc in Applied Information and Data Science?

Coding with Python and R! Before I started studying, I couldn’t imagine how much pleasure is hidden in a functional piece of code.

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What are the biggest challenges in your job at the moment?

Our customers’ IT managers are looking for interactive and dynamic dashboards, but our prospective users generally like to keep working with static reports and evaluations. Finding a satisfying middle ground in such situations is among the biggest challenges in my job at the moment.

What advice would you give to others starting out in the same role?

For me, starting in the new job meant facing a lot of unknowns: New tools and technologies, new clients from unfamiliar business sectors, new methods and processes. And a lot of new abbreviations! My advice to others who may be in such a situation: Be patient with yourself! Enjoy discovering and trying things out, and if you get stuck, make sure you have a good team to support you.

And finally: What new hashtag are you aiming for?

After completing my MA in Applied Information and Data Science last year, I decided to take a break from studying. In the meantime, however, I’m realizing that I need a new challenge, which why I use the #whatsnext hashtag.😊

We thank Irma Glatt for her dedication and time to share these valuable insights with us.

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Data Scientist Professional Portrait

Professional Data Science portrait with Xiying Liu: Specialist

An inspiring personality with a passion for lifelong learning, creative ideas and new solutions – that is Xiying Liu. Xiying works as a specialist in the Ancillary Services and Analytics team at Swissgrid, the transmission system operator in Switzerland. Find out more about our HSLU Master in Applied Information and Data Science graduate Xiying Liu and her inspiring career in the interview below.

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Xiying Liu
Specialist @ Swissgrid AG and
Applied Information and Data Science Master’s graduate @HSLU

First of all, tell us something about yourself: What hashtags best describe you?

#Learner
#Ideator
#Developer

Tell us more about them:

#Learner: I believe in lifelong learning, am curious and often find interesting things to learn. For example, history, cultures, foreign languages, Data Science, etc. I also meet a lot of interesting people while learning different subjects. Both learning and sharing with these people has broadened my perspective and even helped me make some life-changing decisions.

#Ideator: I love coming up with new and revolutionary ideas to challenge established but outdated ideas. Starting new things or ventures, pushing innovative ideas and making positive changes is satisfying to me. My belief is that the world is in a state of constant change. And I believe that I can be a part of that change, even from a very small perspective.

#Developer: I enjoy developing new things at work, such as new processes, models or solutions. These can bring good ideas to life and add value to the working environment. One of the most exciting things about being a developer is being at the forefront of change and building new things.

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Now let’s talk about your professional life: What do you do at Swissgrid?

I work as a Specialist in the Ancillary Services & Analytics team at Swissgrid. The Transmission System Operator (TSO) in Switzerland, Swissgrid, has a legal obligation to procure ancillary services. These services are essential to ensure a continuous balance between consumption and production, using market-based processes. One of the main tasks of our team is the procurement of ancillary services. They require various operational tasks, including coordination and cooperation with internal and external stakeholders in the energy sector.

I also have more data-oriented tasks, such as historical data analysis, time series forecasting and the necessary data engineering tasks. For example, we need to evaluate the results of the procurement of ancillary services. This involves understanding the electricity market and the behaviour of market participants. In addition, we support and improve decision making in our operations based on data analysis and forecasting. To accomplish these tasks, we typically start by identifying the critical questions. Then we collect and clean the relevant data. In the end, we select the methodologies (i.e., optimisation or forecasting methods) to analyse the pre-processed data. Finally, we visualise the results to communicate with the various stakeholders and define further activities. Real-world data science work is often an iterative process involving continuous cycles of some or all of these steps.

What have you done before and why did you join Swissgrid?

I have worked in different sectors and in different countries. Most of my experience has been in academic and research work in the energy sector. For example, I have worked on energy and climate policy in China and South East Asia and on global carbon emission estimation, etc. The main reason for joining Swissgrid is that it fits well with my passion and expertise in energy and Data Science.

Tell us about the most exciting part of your job.

The most exciting part of my job is developing innovative data-driven solutions for the business. I work in the energy sector, which is at the heart of sustainable development in our society. On the one hand, conventional infrastructure and established processes have built it for more than a century. On the other hand, many innovative and disruptive technologies have shaped and changed it dramatically by recent decades. I see great potential in the energy sector. It can apply many of the latest Data Science concepts and methods to significantly improve the performance of decision-making and day-to-day operations. I get to work on a lot of interesting questions from different teams, work with large amounts of data and explore new Data Science solutions. It is exciting to be part of this fast-paced development.

What Data Science skills are most in demand in your role?

Firstly, time series data is one of the most common data types in the energy sector. Therefore, it is necessary to understand how to work with it to perform various analysis and forecasting tasks. Secondly, visual communication skills based on well-designed visualisation are in high demand. Visualisation is not where data analysis ends. It is where data analysis begins to work in real life. Excellent visual communication can not only reveal and communicate the insights of data analysis efficiently, but also influence decision making. Third, data engineering plays a fundamental role in our daily work with data, as all data-related tasks rely on well-designed and executed data pipelines. As a result, Data Engineers and Data Scientists with strong data engineering skills are increasingly in demand.

Do you see yourself as a technician or an analyst? Or a creative genius, management superhero or generalist wizard?

It is difficult to define myself in one role. I think everyone has multiple dimensions. Depending on the question, I would say I am a combination of a technician and an analyst. I have creative ideas and Data Science skills. By learning how to use management skills and mobilise available resources, I am able to answer questions and solve problems. Today, many positions require different roles from the same person doing the job. One set of skills cannot solve all the problems.

I find it helpful not to pre-define certain roles for myself, so that the ideas in my head do not unconsciously limit me. Now I think in a slightly different way when working in a team. Since each team task requires a specific set of skills and roles from team members, I tend to define my role based on the comparative advantages of each team member’s expertise and the agreement of all members.

What do you remember most about your time on the MSc in Applied Information and Data Science?

The answer can be long because my time at HSLU was two years full of unforgettable memories. The most important thing that happened during this time was that I became a mother. I was lucky to have support from home, work and the Master’s programme at HSLU. My daughter was also incredibly supportive of me coming over the winter break. So I didn’t have to miss any classes or exams. Still, it was an extremely challenging experience. I had never imagined how difficult it would be to look after a newborn baby and myself while studying and working.

After dealing with many physical limitations and mental pressures, I am proud of myself for graduating with the recognition of being the best student. But of course it is not just about me. I could never have done it without the support system around me. This experience made me realise how difficult (sometimes impossible) it is for women, especially mothers, to pursue their own goals on top of raising a family and fulfilling the responsibilities that society expects of them.

Often we have a seemingly equal system for men and women. But in many cases it can be unfair. For example, if everyone needs to attend courses, a father with a newborn baby would have a better chance of attending in person than a mother with a newborn baby. It is more inconvenient for the latter to travel. In order to encourage and support more female students to complete their studies, it would be helpful and highly appreciated if the Master’s programme or even the university could take more account of their actual needs. For example, more flexibility depending on the individual case (instead of a one-size-fits-all policy) and more on-site infrastructure support, such as breastfeeding rooms.

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What are the biggest challenges in your job at the moment?

Firstly, working with real-world data is always challenging and time consuming. There are very few shortcuts and you have to learn by doing. What might help is to establish an effective learning process for working with real data based on your own experience and to develop best practices step by step. Second, daring to ask questions and selecting the most valuable ones to answer is important but difficult, especially for new Data Scientists. Learning from colleagues around you who have more experience or can spot the critical points is one of the most effective ways to grow. Third, collaborating and coordinating with different stakeholders to achieve project goals is always challenging. Therefore, effective communication skills are essential for Data Scientists to understand real business issues, find cross-team solutions, communicate the results and bring their ideas to life.

What advice would you give to others starting out in the same role?

Get your hands dirty. Get involved in real-world projects and Kagal competitions, contribute to GitHub repositories. This can be a solid and efficient approach to strengthening your Data Science skills. In the meantime, try to find a project that interests you. If one does not exist, feel free to create one. You may be surprised to see where your ideas can take you. Perhaps the best way to work with data is to see how you can do it with fun and personal interest.

And finally: What new hashtag are you aiming for in 2023?

#open – to not let preconceptions limit myself and to open my mind and heart to new possibilities.

We thank Xiying Liu for her dedication and time to share these valuable insights with us.

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