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New member of the team: Andreas Franz

Andreas

Andreas |

22. Juli 2019 |

- min Lesezeit

New member of the team: Andreas Franz

Andreas joined us in January 2019. Find out more about his background and work at DieProduktMacher here.

My Background

My path towards Data Science started off as a mathematics student at Ludwigs-Maximilian-München. At the beginning of my studies, I was really more interested in foundational topics like algebra, logics, proof-theory, type-theory or theoretical computer science. After a while, I also wanted to apply my learnings in practice. Therefore, I started to learn programming and finished my first software projects, initially in more exotic languages like Agda, Scheme or Haskel, which were more similar to what I already knew at the time. Two of my favorite projects where a theorem-prover for propositional logic (arguably my first AI project), as well as a program for doing exact real arithmetic using gray-code computation. I was not actively pursuing Data Science then, apart from learning about things like statistics or probability, but my interest in computers was definitely awakened, which led me to the next chapter of my journey.

My professor, who saw how much fun I had coding, pointed me to a seminar for discrete mathematics. Part of this seminar consisted of applying genetic algorithms to combinatorial problems and, during my research, I grew more and more interest in the field of Data Science as a whole. I still remember my fascination, when I trained my first word-embedding model. It really felt like my pc was getting somewhat smart. I was hooked! I spent half my semester break learning more about Data Science, coded like crazy in python and R and still wanted to learn more. I was getting quite good and was able to land a job as a working student. After I finished my studies, I became a full-time Data Scientist at the same company, mainly working in the area of natural language processing and business intelligence.

What I liked most about the position there was that I was able to put both, my experience in writing software, as well as my knowledge of Data Science to good use, since I was included in every step of the product development from ideation to defining the requirements, prototyping up until the point where we would put the things in production. Actually, I especially miss working with our exceptional backend programmers, who taught me what it means to scale and also how it is done. They also introduced me to Scala, which is still one of my favorite programming languages.

Work @DPM

One of the reasons I decided to work @DPM was that I expected a broad range of different projects that would help me to grow professionally. My expectations were met during my first few months here, already. Our topics are as diverse as the people who work here. They range from simple Data-Analysis to recommender-systems, natural language processing, IOT, speech recognition, and object detection. It is partly because of the diversity of topics, that we are encouraged to explore trends and new technologies constantly. It has been only a few weeks and I have already visited a Data Science conference and participated at a Hackathon with a few of my colleagues (unfortunately we did not win the 1st price, but it was fun nonetheless). On our “crazy Friday”, a day to learn and have fun, we explore the most trending topics in a variety of contexts, which I find most important, especially in a fast-growing field like Data Science, where you can find a new, interesting paper every day.

I also like to get my hands dirty sometimes, dig through the code, challenge each other’s ideas and to reach that sweet spot, when things just seem to work magically. I love the fact that @DPM, people have a very similar mindset: we want to enable our customers to develop new, innovative ideas, but also help to bring these things to live! This hands-on mentality is exciting as well as challenging at times, as it requires to keep an eye on the big picture constantly.

So far I am more than happy with my new job, I love my colleagues here and I look forward to the next challenges my team and I will be tackling together.


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