Munich Re is looking to leverage machine learning to transform the life insurance industry by enabling easier access to insurance and promoting healthier lifestyles. The company aims to build scalable products with strong security and ML/DevOps practices, research bias and fairness, disease models, and NLP to drive innovation and improve core processes.
Requirements
- Expertise in advanced predictive analytic techniques;
- Fluency with SQL, Python, or R;
- Demonstrated experience working with analytics through the modeling lifecycle including gathering data, design, recommendations, testing, implementation, communication, and revisions;
Responsibilities
- Apply statistical and machine learning techniques to assist with building models for underwriting, pricing, and claims management;
- Help us drive innovation, enabling new underwriting paradigms, distribution models, and data management;
- Build and implement solutions that enable operational units to improve quality and speed of core processes in order to generate incremental revenue or reduce expense;
- Proactively research new ways of modeling data to unlock actionable insights or improve processes;
- Collaborate across Munich Re functions and with clients to use analytics to influence business decisions;
- Network with existing data science groups at Munich Re – collaborate with internal partners at our Munich Chief Data Office to leverage capabilities in big data technology.
Other
- You will be expected to relocate to the greater New York area, to meet our hybrid working model of at least 3 days a week in office.
- Degree in Computer Science, Statistics, Data Science/Analytics, Applied Mathematics, Engineering (Physics, Bioinformatics) – or equivalent program offering coursework manipulating large datasets;
- Graduate degree (Master’s, PhD) preferred
- Excellent communication skills; spoken & written, formal/informal presentation – to effectively interpret and present actionable insights to partners;
- Resourceful and able to learn quickly;
