01.06.2022 | Get to know our trainees: Nicolas Pelzmann

I learn from every challenge I face

Nicolas Pelzmann completed his bachelor's degree in Mechanical Engineering in Vienna and his master's degree in Robotics, Systems and Control at ETH Zurich. After graduating, he wanted to explore different lines of business and be able to work on a broad range of topics. That's why he joined Axpo’s trainee program, which gives him an insight into three different functions. Since October 2021, he has been working as a Data Science & Data Engineering Trainee on various tasks and challenges.  

Nicolas Pelzmann

Function: Trainee Data Science & Data Engineering Power

Background: MSc in Robotics, Systems and Control, ETH Zurich  

Assignments: Grid 4.0, Optimization, tbd

Why did you start your traineeship at Axpo?

After finishing my studies, I knew that I wanted to experience different areas of work and get a diverse overview of various fields, before choosing a permanent position. The traineeship provides me with the breadth I was looking for, while allowing me to grow with each challenge I face.

What are the benefits of a traineeship from your perspective?

As a trainee, you are given a lot of freedom to explore topics beyond the daily business of the departments you work in. You can focus on areas of particular interest, and work on topics that could have a significant impact on how the business operates.

Can you tell us more about the different rotations and projects during your traineeship?

In my first rotation, I implemented a machine learning-based voltage prediction for shunt reactor switching in substations. The prediction helps to reduce the number of on-off switches, and therefore the wear and tear on system components, while helping with power grid stabilization.

In my current rotation, I am working on improving estimates for current and future inflow into hydro-powerplant basins. The quality of inflow estimates and predictions have a significant impact on the operation of Axpo’s powerplants, and consequently efficiency and reliability of Swiss energy supply.

 

Nicolas together with some of his colleagues from the Grid 4.0 team.

What mark did you leave behind during your traineeship? What is your “foot print”?  

I implemented a machine learning algorithm, together with the first MLOps platform for auditable model deployment and operation at Grid 4.0.

What is a typical day at work as a trainee at Axpo (highlights of your working day)?

One of my highlights is providing a programmed working solution that solves a problem for someone and makes their life easier.

What was something you didn’t know before you started working at Axpo?

There are definitely a myriad of things I did not know, and probably many more I still don’t know. I always took grid operations for granted, and never thought about how much manpower actually goes into keeping the lights on. Electricity has become something we all take for granted. It’s just there – well until it isn’t, that is.

What can you apply in your daily work, that you learned at university?

As a data science trainee, all the machine learning-related courses I took at university, in particular the associated programming skills, are extremely important to my everyday work. Additionally, the ability to quickly pick up new skills thanks to a solid analytical skillset, is proving crucial time and time again.

What do you recommend to graduates for their career start?

Try to make up your mind about what it is you want to do in your career, and what you don’t want to do. Do you like programming, interacting with people, getting really deep into one topic, or being more of a generalist? Go through the “classical recruiter questions” and answer them honestly – although a nuisance, they help with the process. Also, be aware that no single job can offer it all: becoming an expert in one field means you can’t dip into many different areas. It is your responsibility to truthfully figure out what it is you want to do in your career and pursue it.

Did Nicolas’ experience with his traineeship at Axpo spark your curiosity? You can find more information about it here. We look forward to hopefully meeting you during the recruitment process!

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