(Senior) Data Scientist for Pricing Actuarial Services | (Senior) Data Scientist für das Pricing Aktuariat (m/w/d)
Allianz Deutschland AG
Job Summary
As a (Senior) Data Scientist within the Pricing Actuarial department at Allianz, you will play a pivotal role in shaping insurance tariffs for property and casualty products in Germany. Working within an agile, cross-functional team, you will take end-to-end responsibility for developing scalable Machine Learning and Deep Learning solutions. Your daily tasks will include data exploration, designing high-availability ML workflows on cloud platforms like AWS and Snowflake, and operationalizing Generative AI systems. This role bridges the gap between traditional actuarial expertise and modern big data infrastructure, allowing you to derive actionable insights from one of the industry's largest datasets. The position is particularly attractive due to its blend of strategic influence, hybrid working model, and the opportunity to work at a globally leading insurer that consistently ranks as a 'Great Place to Work'. You will be at the forefront of cloud ML strategy and the implementation of agent-based systems in a production environment.
Required Skills
Education
Excellent degree in Data Science, Machine Learning, Mathematics, Physics, Computer Science, Statistics, or a comparable field of study. A PhD is considered an advantage.
Experience
- At least 2 years of practical experience in Statistics, Machine Learning, and optionally Deep Learning
- Professional experience in modern engineering techniques and cloud data platforms
- Practical experience in Property & Casualty insurance mathematics is preferred
- Experience in agile project environments and taking end-to-end responsibility
- Experience in developing scalable and high-availability ML solutions
Languages
Additional
- The role is based in Germany with a hybrid working model. Candidates must have the ability to work in agile, cross-functional teams and possess strong communication skills to explain complex technical topics.
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