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Consultant Data Science @Munich Re | Reviewer for ICLR and NIPS | Causal Inference & Causal Modelling
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Assessing your cultural and operational fit
Consultant for Data Science and Data Engineering | Causal Inference & Causal Modelling | Reviewer for ICLR and NIPS.
Ludwig-Maximilians-Universität München
Master of Science (M.Sc.), Elite Master Course - Theoretical and Mathematical Physics
January 1, 2016 – January 1, 2018
Ludwig-Maximilians-Universität München
Bachelor of Science (B.Sc.), Physics, Mathematics
January 1, 2013 – January 1, 2016
DHBW Mannheim
Bachelor of Arts (B.A.), Business Administration - Automotive Commerce
January 1, 2010 – January 1, 2013
HSB - Hartford Steam Boiler
Cyber Data Science - Hartford Steam Boilers
August 1, 2025 – November 1, 2025
Hartford, Connecticut, Vereinigte Staaten von Amerika · On-site
Munich Re
Consultant Data Science - Central Data and Advanced Analytics
December 1, 2022 – Present
München, Bayern, Deutschland
b.telligent
Team Lead Data Science & AI
July 1, 2021 – September 1, 2022
b.telligent
Senior Consultant - Data Science & AI
January 1, 2021 – September 1, 2022
b.telligent
Consultant - Data Science & AI
April 1, 2019 – December 1, 2020
Max Planck Institute for Astrophysics
Research Scientist
October 1, 2018 – January 1, 2019
München und Umgebung, Deutschland
4tiitoo GmbH
Machine Learning Developer
November 1, 2014 – October 1, 2017
München und Umgebung, Deutschland
Sixt rent a car
Student dual study program
October 1, 2010 – September 1, 2013
Pullach (Munich), Palma de Mallorca
Microsoft Certified: Azure Data Scientist Associate
Microsoft
June 24, 2026 – Present
Microsoft Azure Fundamentals
Microsoft
June 24, 2026 – Present
AWS Certified Machine Learning Specialist
Amazon Web Services (AWS)
June 24, 2026 – Present
AWS Certified Cloud Practitioner
Amazon Web Services (AWS)
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse professional background spanning consulting, research, and corporate roles in different companies (b.telligent, Munich Re, HSB). Their academic background in physics and business administration, combined with practical experience in various data science applications (customer analytics, geoanalytics, cyber data science), suggests a broad perspective and adaptability. The target role of 'AI Engineer' aligns well with their MLOps and ML development experience, indicating a good cultural fit for a technically advanced and collaborative environment.
Soft Skills & Operational Fit
The candidate's experience as a Team Lead and Product Owner suggests strong leadership, coordination, and communication skills. Their consulting background implies adaptability and client-facing abilities. The focus on MLOps indicates an understanding of operationalizing ML solutions.