Workster is partnering with a global leader in the mobility industry to recruit a Senior Data Scientist – Reinforcement Learning (m/f/d) for their growing Data Science & Engineering team in Munich. This is a high-impact opportunity to shape the future of intelligent pricing systems through advanced probabilistic modeling and state-of-the-art machine learning techniques.

You’ll be joining a company that values rigorous science, scalability, and innovation—where your models will directly influence millions of real-time business decisions across global markets.

Your Role

• Architect and prototype Bayesian regression models (GLM, mixed-effects, Gaussian Process) to support dynamic pricing strategies.
• Implement techniques like SVI, MCMC, and importance sampling to make robust decisions under uncertainty.
• Design and maintain feature engineering pipelines and automated data validation using tools such as Airflow or Dagster.
• Deploy production models via FastAPI, Docker, and Kubernetes, ensuring performance monitoring and anomaly detection are in place.
• Design and evaluate A/B and multivariate tests using causal inference and quasi-experimental methods.
• Collaborate cross-functionally with revenue and product teams to turn abstract ideas into data-driven hypotheses.
• Mentor team members and help elevate internal Bayesian and modeling standards through workshops and publications.

Your Qualifications

• 5+ years of experience in applied statistical modeling, with a strong focus on Bayesian methods.
• Proficiency in probabilistic programming using PyMC, Stan, NumPyro, TFP, or similar tools.
• Hands-on experience with SVI, black-box variational inference, and large-scale MCMC techniques.
• Strong Python programming skills with best practices in testing, type hints, and CI/CD.
• Familiarity with cloud infrastructure (AWS, GCP, or Azure), Docker/Kubernetes, and workflow orchestration tools.
• Excellent communication skills—able to explain statistical concepts and uncertainty to both technical and executive audiences.

The Offer

• A hybrid working model with flexibility and 30 days of paid vacation.
• Opportunities to engage in company-wide learning initiatives and volunteer days.
• Access to on-site fitness and leisure facilities in a modern workspace.
• Mobility support, pension contributions, and generous employee discounts on mobility services.
• A supportive and collaborative team culture with cutting-edge technologies and complex real-world challenges.

Benefits