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

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.


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.


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.

Monday, 12 August 2024, online, English
Monday, 9 September 2024, online, German

PROGRAMME INFO: MSc in Applied Information and Data Science
MORE FIELD REPORTS & EXPERIENCES: Professional portraits & study insights

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