Women in Big Data is spotlighting amazing women.

Julia Kannenberg, a data scientist at Henkel, a German chemical and consumer goods company, holds a diploma in social science and a bachelor’s in statistics.  She has previous work experience in consulting and biostatistics, and takes the time to share some insights with our network.

I currently work as a Data Scientist at Henkel, a German chemical and consumer goods company. Within Henkel I’ve been working on a variety of use cases ranging from unsupervised learning to classification models based on machine learning methods and AI applications to automatically extract data from documents. I love writing code and mainly use Python and adjunct libraries like pandas, scikit-learn as well as PySpark. I’m especially enthusiastic about bringing machine learning workflows to production using Cloud Technology and applying software development best practices in the Data Science Lifecycle.

After graduating high school I actually studied social science. My goal back then was to work for an NGO or international organization like the Red Cross, WHO or Amnesty just to name a few: I‘m from a small village in northern Bavaria and I really wanted to see the world!

Soon into my studies, I realized I enjoyed the statistics and data analytics courses much more than the ones on political science. My focus areas in high school were math and physics…and yes, full disclosure here: I was also this kind of nerdy teenager who joined extra-curricular activities like solar physics. I realized I really enjoy working in a structured way and testing different methods to solve a problem. Pursuing a career in data science felt like going back to my roots.

I decided to get a second degree in statistics, as I wanted to have a solid background in math and programming. This turned out to be one of the best decisions I have  made in my life. After graduation and traveling around the world for a year, I landed my first job in the Chile office of an international consulting company working for a client in the US in a team with colleagues from India, Chile, and Colombia…19-year-old me would have been kind of proud.

What motivates me – What I enjoy most about my job is constantly engaging with new technologies. Almost every day I learn something new that helps me do my job better. I use libraries and frameworks developed by some of the world’s smartest people: they are just one git clone or pip install away.

Sometimes it’s challenging to keep up to date with what is state of the art: You’re in the team meeting and then suddenly there is a lively discussion going on about a new package, tool, optimization method, algorithm, etc. you’ve never heard of and you start wondering if you missed something important going on in data science.

On the other hand, I’ve just learned something new… and for me that is what counts at the end of my day. It leads me further to my goal of being an awesome machine learning engineer.

Key takeaway from my career: Others are a great source of inspiration and motivation, the best you can do is stay true to yourself and you follow the path you’ve set, may it be becoming an awesome data scientist, product owner, analytics manager, scrum master or whatever career path you see for yourself. Let’s cheer each other on, while we walk our paths!