Senior Data Scientist (Reinforcement Learning)

Das ist der Job

Implement techniques like SVI, MCMC, and importance sampling to make robust decisions under uncertainty.

Darum lohnt es sich

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. 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. Access to on‑site fitness and leisure facilities in a modern workspace.

A supportive and collaborative team culture with cutting‑edge technologies and complex real-world challenges. #J-18808-Ljbffr 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.

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. 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.

Mobility support, pension contributions, and generous employee discounts on mobility services.