Experience:
I am a physicist and data scientist with 4 years of professional experience in applying machine learning to improve data-driven marketing analytics. I developed state-of-the-art machine learning models for use cases such as customer value prediction, customer segmentation, marketing engagement and churn prediction. Moreover, I consulted various specialist departments on using data science to solve different business problems. Thereby, I developed and validated machine-learning models in numerous proof-of-concept studies. I also supported the machine learning engineers and software developers with the deployment and monitoring of the models. Before transitioning into the world of data science I worked as an academic researcher for 10 years and gained deep insights into medical physics, medical imaging, signal processing, mathematics, statistics and regression analysis.

My Value Proposition:
- consultation on marketing analytics use cases such as customer value prediction, customer segmentation, sales prediction, marketing engagement and churn prediction
- supporting specialist departments to translate business questions into well defined data science use cases
- implementing an evaluating model prototypes
- presenting the key analytical findings in a clear and understandable way to both technical and non-technical audiences
- supporting the development team with the deployment of the models