Professional Portrait with Lisa Becker: Controlling Professional & Data Science Specialist

Professional Portrait with Lisa Becker: Controlling Professional & Data Science Specialist

With Lisa Becker, former HSLU and data science student, we were able to portray another interesting job description. Lisa Becker works as a Controlling Professional & Data Science Specialist at Siemens. She is responsible for the development of several databases and business intelligence systems as well she takes care and is supporting AI pilot projects. Read her interesting insights into her daily business and Data Science studies here.

Lisa Becker
Controlling Professional & Data Science Specialist

First of all, tell us about yourself: Which hashtags describe you the best?
#explore #simplethings

If you like: Tell us more about them.
I am always open to new things, be it a new hobby or a new method that I can use in my everyday work. I’m always happy about changes and having a chance to try things out.
I always try to keep everything as simple as possible and not to complicate it unnecessarily. Complexity is something that usually comes by itself.



Now let’s talk about your professional life: What do you do at Siemens?
I am responsible for developing a number of databases and business intelligence systems. I also get to work on AI pilot projects and see them through to the end.

What did you do previously and why did you join Siemens?
Before I started at Siemens, I worked exclusively in the field of controlling. Today, my knowledge from the specialist area is a big help when it comes to developing data models with a financial background.

Tell us about the most exciting thing in your job.
I’m in contact with all kinds of people from many different departments. Siemens also gives me a lot of freedom when it comes to developing new things, and I can try things out and be creative. Of course, not every idea ultimately works, but that’s part of the fun.

Which data science skills are especially in demand in your job?
Communication is enormously important, in addition to technical knowledge. Most stakeholders don’t have a technical background and understanding their needs and coming up with solutions correctly is often a challenge. On the other hand, you have to be sensitive when explaining technical problems in order to convince also those stakeholders who are not computer scientists. Having a solid grasp of organizations and project management is also an advantage. In everyday work, data projects tend to run in parallel. So, maintaining an overview and identifying or adjusting priorities at the right moment can make a world of difference.

Do you think of yourself more as a techie or as an analyst? Or as a creative genius, management superhero or generalist wizard?
I think I would describe myself as a generalist. My strength lies in being able to efficiently analyze problems and quickly familiarize myself with new topics. I see this as a great advantage, especially in the field of data science, where each project is likely to be unique.

What do you remember the most when you look back at your studies (MSc in Applied Information and Data Science)?
I am particularly excited about the range of options that data science offers. It’s a field that is constantly developing. I keep coming across new methods and tools that I had never heard of before but that can be applied in many ways.

What are the biggest challenges in your job at the moment?
For me, the biggest challenge is to keep cool when things get hectic. You should never underestimate the number of projects and the many different stakeholders you may be dealing with. It’s not always easy to stay calm and keep an overview of all that’s going on.

What advice would you have for others starting in the same job?
Try out new things and don’t let failures get you down.

And finally: What new hashtag are you aiming for in 2021?
#backtobasics  In our studies we covered many technologies and methods, some of which I can already use in my everyday work at Siemens. In 2021, I would like to try out some additional skills from the data science toolbox.

Many thanks to Lisa Becker for this informative interview and interesting insights into your job!

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