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Professional Portrait - Internal Audit Manager, Data Analytics Leader with Pascal Himmelberger, Swiss National Bank

Our former HSLU and Applied Data Science student Pascal Himmelberger is working at the Swiss National Bank as "Internal Audit Manager, Data Analytics Leader". Creativity, innovation and fearlessly plunging into the unknown are some of his strong characteristics. Read more about Pascal Himmelberger's professional life with a look back at his studies with us.  

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Pascal Himmelberger 
Internal Audit Manager, Data Analytics Leader @ Swiss National Bank

First of all, tell us something about yourself: Which hashtags describe you the best?
#creativity #innovation #exploration #pragmatism #unlockingpotential #goyourway

Tell us more about them. 
- #creativity and #innovation in technology and business have always fascinated me and are things I'm very comfortable with because they call for an explorative and iterative approach. In other words, I like simply trying something out, venturing onto new territory and making continuous improvements.
- However, creating value (#unlockingpotential) also means being pragmatic and having the ability to actually implement and realize things.
- Truly new ways and approaches call for a broad perspective and lots of experience. To innovate, you need to work with unique, knowledgeable and experienced people who will help you go your own way.  

Now let's talk about your professional life: What do you do at the Swiss National Bank?
I am a manager in the internal audit unit, which means I'm responsible for setting up and developing the bank's data analytics. On the one hand, I help to prepare data and analyses so that the bank can use them for its auditing work; on the other hand, I review and ideally improve its existing data and analytical activities.

What did you do previously and why did you join the Swiss National Bank?
Previously, I worked for various consulting companies in the field of data analytics. I specialized in intelligent automation and forensic data analytics and thus spent a great deal of time on such projects. Before being a consultant, I worked as an IT auditor at a large auditing company, where I learned a lot about various analytics topics, and this in turn further sparked my interest in the field. I joined the SNB because it gave me the rare opportunity to set up and develop the area of data analyses in an exciting institution pretty much from scratch.

Tell us about the most exciting thing in your job.
In addition to the opportunities mentioned above to establish analytics as a core theme at the SNB, I also have the chance to experience all aspects of a truly unique institution. I find it motivating to contribute to the success of an institution with such an important national function.

Which data science skills are especially in demand in your job?
My role currently requires conceptual and technical skills with which to design and carry out data analyses. This means understanding business and process requirements, developing strategies, setting up the environments and pipelines (databases, SQL, Python, R, data management and engineering) for analyzing data, as well as preparing and visualizing the data (PowerBI, Python Matplotlib, R-Shiny) for a specific stakeholder group.

Do you think of yourself more as a techie or as an analyst? Or as a creative genius, management superhero or generalist wiz?
My interests are very broad. I find many topics around data analysis, innovation, management and technology very exciting and therefore think of myself rather as a generalist.

What do you remember the most when you look back at your time in the MSc in Applied Information and Data Science program?
The degree program had a lot of exciting content thanks to its broad range of subjects, and it gave me as a student lots of room to pursue my interests. I often found data engineering topics relating to infrastructure especially appealing and liked the challenge and excitement of building a pipeline, ideally an automated one, for pre-processing and analyzing data. The additional challenge of managing big data (with its variety, speed and volume) added another level of excitement. The Modern Data Engineering in the Cloud course was definitely a highlight. 

What are the biggest challenges in your job at the moment?
Introducing an entirely new topic in an organization from the very beginning takes a lot of time and thought. Often there's no clear "right" or "wrong." So, the question becomes more a matter of what makes the most sense for the requirements and current situation – and discovering what this involves is not always trivial!

What advice would you have for others starting in the same job?
Contribute what you know and have the courage to question the status quo.

And finally: What new hashtag are you aiming for in 2021?
#keeplearning 

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Data is the resource of the 21st century.
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