Data Scientist

The Data Scientist will join our BI & Data Analytics team and help evolve our healthcare analytics, fraud detection, and actuarial decision-support products. In this role, you will work with real health insurance data, including policies, members, providers, and claims, to develop models that detect fraud and abuse, support pricing and underwriting decisions, and transform complex data into actionable insights for our clients. As our product roadmap expands into AI-assisted capabilities, you will also have the opportunity to contribute to and grow your expertise in areas such as Large Language Models (LLMs) and AI agents.

Responsibilities:

• Develop, validate, and improve FWA detection models, including provider profiling, cost and utilization outlier detection, anomaly detection, network analysis, and time series analysis.
• Build predictive and risk models that support actuarial pricing, underwriting, and claims analytics.
• Explore large claims and policy datasets and collaborate with Data Engineers to deploy models into production and monitor their performance and drift over time.
• Ensure model outputs are explainable and defensible for investigators, actuaries, clients, and other stakeholders.
• Translate analytical findings into features, KPIs, and insights for BI dashboards and client reporting.
• Prototype LLM- and agent-based capabilities, such as analytical assistants and automated investigation support tools, as the product roadmap evolves.
• Collaborate with Product Managers, Data Engineers, and domain experts to transform business requirements into analytical solutions and participate in client workshops focused on data, analytics, and AI.

Requirements

• Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, Data Science, or a related field, or equivalent practical experience.
• Professional experience in Data Science, Machine Learning, or related analytical roles.
• Solid grounding in statistics and machine learning, including supervised and unsupervised methods, model evaluation and validation, and feature engineering.
• Strong Python skills, including experience with data science libraries such as Pandas, NumPy, and Scikit-learn.
• Strong SQL skills and experience working with large relational datasets, ideally within Oracle environments.
• Experience applying anomaly detection, outlier detection, or similar unsupervised learning techniques.
• Experience deploying analytical models into production environments or regular business operations.
• Strong analytical thinking and problem-solving capabilities.
• Ability to communicate complex analytical findings clearly to both technical and non-technical audiences.
• Excellent written and spoken English.

Desired Skills

• Experience with LLMs and AI agents, including prompt engineering, RAG, embeddings, vector search, tool calling, or orchestration frameworks.
• Experience working with health insurance, healthcare, or claims data.
• Exposure to actuarial, pricing, or underwriting concepts.
• Experience in fraud detection, graph analytics, network analysis, and model explainability techniques (e.g., SHAP).
• Experience with PL/SQL and Oracle ML/AI capabilities, such as Oracle Machine Learning (OML) or AI Vector Search.
• Experience with OCI or another major cloud platform.
• Familiarity with Git, Docker, CI/CD pipelines, and FastAPI for model deployment and serving.

Benefits

• Competitive salary and benefits, including but not limited to: life/health insurance, annual company bonus, hybrid work model

• Continuous hard and soft skills development through global platforms & local academy

• Diverse and inclusive culture

• International mobility withing the Munich Re Group

• Enjoyable and stable working environment

• Leading-edge technology

About Us

Munich Re HealthTech S.A., a division of Munich Re, is a leading global specialist in digital solutions for the health insurance industry.

Munich Re HealthTech has been operating since 1995 and its solutions currently support 26 organizations in 19 countries in Europe, the Middle East, Africa and Latin America. Its software solutions decrease the complexity of creating and managing complicated health insurance products, enhance the customer experience throughout the claims process and provide the tools for successful portfolio management.