After finishing my bachelor’s degree, I wanted to pursue a master’s degree in data science. There were master’s with a focus in data science available, however, they were aimed at students with a background in math or informatics, therefore, I didn’t meet the entry requirements. In parallel, I applied to different companies, mainly in the banking domain, for risk management positions with a quantitative focus. It didn’t take long and I received an offer for a position in the Risk Analytics department, which I accepted.
During my employment, I continued looking for a master’s in the field of data science and found the Master in Applied Data Science programme of Frankfurt School. A huge advantage of the programme was that it enabled me to continue working while pursuing a master’s degree thanks to the 3-day-model. I had talks with my employer about whether they would support me from a financial point of view and allow me to work only part-time from Monday to Wednesday since lectures would take place from Thursday to Saturday. My employer agreed and Frankfurt School accepted me as part of the first intake of the Master in Applied Data Science programme.
I really enjoyed my time at Frankfurt School. We were very warmly welcomed and our student advisors took excellent care of us. Coming from a state university, this was a very nice experience. Additionally, since we were the first intake, we were only 16 people who made the classes very interactive. I already had some experience in machine learning through online courses, so I could take away a lot from the courses by asking all the questions that I couldn’t answer myself. The courses had a practical focus while at the same time building up the theoretical foundations of how algorithms work etc.
There were also many projects where my classmates and I were collaborative, which was a great experience, especially as we all had very diverse backgrounds and everybody brought a different skill set to the table. Frankfurt School did a great job in putting together people from various countries, backgrounds and different amounts of work experience. Some people just continued studying right after their bachelor whereas some of us already had a couple of years of work experience. Just like it is the case later on when working at a company.
After finishing the master’s programme, I decided to switch companies and joined a newly founded company called vent.io as a Data Scientist in the Product Engineering team. At vent.io, we work together to get the most out of digital business models and drive them forward. We develop, research and invest in innovative digital solutions for asset-related services. Therefore, we work closely with start-ups from the B2B environment. Furthermore, we build digital touchpoints ourselves and work on data science use cases for asset finance.
In my new position, I’m able to make use of the knowledge I gained during my studies. I’m currently working on a use-case with the goal to predict the new business volume in the upcoming month and quarter. The problem is tackled by combining a classification model and a regression model. The classification model is used to predict the probability that a customer accepts the offer he received. By multiplying this probability with the offer volume, an expected business volume is determined. This output is then fed into a regression model that actually forecasts the new business volume in the upcoming month. As soon as a final model is developed, the goal is to implement the model for production in our cloud environment.
All in all, I’m really thankful that I could be part of this journey at Frankfurt School and that I was able to meet lots of nice people during my studies, who made this experience special.