Data Scientist – Reinforcement Learning (Lisbon)

About the role

We are looking for a senior Data Scientist specialized in Reinforcement Learning to join a global mobility‑tech leader’s tech hub in Lisbon. You will design and deploy advanced statistical and decision‑making models that power millions of dynamic pricing decisions each day.

Key responsibilities

• Prototype regression‑based pricing models (linear, GLM, Gaussian Process, mixed‑effects) within a Bayesian framework.
• Apply scalable inference techniques such as SVI and MCMC on large, streaming datasets.
• Extend multi‑armed bandit algorithms with contextual features and richer priors.
• Build end‑to‑end pipelines for feature engineering, label generation, and automated data quality checks using Airflow or Dagster.
• Package and deploy models as modular services with FastAPI, Docker, or Kubeflow.
• Set up monitoring dashboards and Bayesian control charts to detect data drift and anomalies in real time.
• Design and analyse A/B or multivariate experiments, applying causal inference when needed.
• Collaborate with product managers and analysts to translate complex questions into measurable business impact.
• Mentor peers, share internal technical insights, and lead workshops on Bayesian workflows.

Required profile

• 5+ years of experience applying regression, hierarchical or state‑space models in production.
• Strong expertise in Bayesian modeling and probabilistic programming.
• Hands‑on experience with variational inference and advanced MCMC at scale.
• Solid software‑engineering mindset with Python, type hints, testing and CI/CD best practices.
• Proficiency with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes).
• Excellent communication skills for presenting uncertainty, lift and risk to technical and executive audiences.

Required skills

• Python
• PyMC, Stan, NumPyro, TensorFlow Probability
• Airflow, Dagster
• FastAPI, Docker, Kubeflow
• AWS, GCP, Azure
• Kubernetes
• CI/CD, type hints, testing

What we offer

• 28 vacation days per year plus birthday off and a volunteer day.
• Hybrid work setup with flexible hours and no dress code.
• Private health insurance.
• Coverflex benefits platform and discounts on transport and travel.