Professional Data Science Portrait with Leo Rettich: Data Scientist, Zürcher Kantonalbank

Shortcuts: Interview – Info-Events – Programme Information – Contact – Professional Data Science Portraits

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

#NeverStopLearning
#LeoGoesDataScience

Please tell us more.

About #NeverStopLearning: Whether in my private life, at work, or in a training course, it’s vital for me to keep learning and improving daily. This makes me feel fulfilled, that I’m doing the right thing, and that I’m staying on the ball. It’s also why I’ve been attending further education courses for as long as I’ve been working, most recently the MSc in Applied Information and Data Science at HSLU.

About #LeoGoesDataScience: After working for around ten years as a software developer, I set myself the goal of making data science part of my personal development plan, not only in terms of training but also professionally. Thanks to an internal transfer to a data science team, which my line manager communicated at the time as “Leo goes Data Science,” I reached this goal a few months ago and have since been taking my first steps in this field at Zürcher Kantonalbank.

 

What do you do at Zürcher Kantonalbank? 

As a Data Science Lab team member in the Value Stream Information Management unit, I develop key data science skills and tools within Zürcher Kantonalbank. We implement use cases for the IT, Operations, and Real Estate units and help others with their data science projects.

What did you do before, and why did you join Zürcher Kantonalbank?

I have been with Zürcher Kantonalbank for almost 15 years, including my years as an apprentice. So, the question should rather be why I’ve stayed with Zürcher Kantonalbank for so long. Well, the bank has an excellent corporate culture and strongly emphasises employees’ personal development, which certainly has contributed to my staying in this job all these years. In addition, the IT unit at Zürcher Kantonalbank offers an exciting range of career options. Over 1,000 IT employees work on numerous innovation and digitalisation projects in Zurich’s District 5 and ensure that one of Switzerland’s largest universal banks runs smoothly.

What’s the most exciting part of your job?

I love not only to dive deeply into the content we need when managing data from the various disciplines but also to tackle the technically demanding challenges that data science offers. What also fascinates me about my job is the chance to regularly explore perspectives and options for applying the latest methods and technologies – and to find out what is possible when we apply them profitably to the valuable data troves and technologies we have in our bank.

Which data scientist skills are particularly in demand in your job?

In the current phase, which involves developing the systems and tools for applying data science, it is essential to understand the full range of choices thoroughly. On the one hand, you need a technical command of the entire data value chain – from data management and data engineering, all the way to analytics and machine learning. On the other hand, you have to keep a constant overview of the latest methods and tools in a very fast-changing environment so that you can incorporate them into the design of Zürcher Kantonalbank’s data systems.

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

With my background as a software developer, I’m certainly more of a techie. I like solving technical problems and am generally willing to take on larger programming tasks. However, I realise that my preference for data science also tends to make me an all-rounder. My studies and job require and encourage me to develop a wide range of skills – from communication, planning, and brainstorming, all the way to very technical things like setting up the IT infrastructure.

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

In general, topics such as machine learning and artificial intelligence are the natural follow-up once you’ve learned to develop software. In contrast to traditional programming, data science doesn’t just involve problems that call for clearly formulated rules. That’s what I find so fascinating and motivating. During my studies, I could apply what I had learned in many applied projects, which covered many areas to immerse myself in. For example, in addition to all the data science methods, I also learned about crime, handball, cryptocurrencies, cancer cells and politics. It’s precisely this combination of content and technology that I find so intriguing about data science.

 

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

The biggest challenge at the moment is organising the systems and tools with which to apply data science to the use cases in our bank. We face many uncertainties at the moment about the IT architecture, tools, IT governance, data protection, the current shift to the cloud, technological progress, and many unclear responsibilities. And it takes a lot of effort to finally become productive with data science.

What advice do you have for someone who wants to follow in your footsteps?

My advice would be not to get discouraged if things don’t move ahead as quickly as expected in a large company like Zürcher Kantonalbank, but to keep at it and trust that your fascination with data science will see you through whatever happens to be in the way.

And finally, what new hashtag are you aiming for?

In Swiss German, we have #zämeMehUsDateUsehole, which basically means working together to get the most out of our data. It’s the official vision of our value stream. For me, it means collaborating within Zürcher Kantonalbank to create real added value from the available data. I still see a lot of potential here to reach this goal fully and would like to contribute more.

We would like to thank Leo Rettich for his dedication and for sharing these valuable insights.

DATA IS THE RESOURCE OF THE 21ST CENTURY!
REGISTER & JOIN US FOR A FREE ONLINE INFORMATION EVENT:
Monday, 13 January 2025, online, German
Monday, 10 February 2025, online, English
Monday, 10 March 2025, online, English