Senior Data Scientist: Bayesian RL & Personalisation

SIXT; Portugal; Hybrid; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Global Tech Hub

Learning events

Flexible work

Vacation days

Health insurance

Meal allowance

Employee discounts

Job summary

SIXT is seeking a senior roles in Lisbon to develop probabilistic models guiding pricing and personalised offers. You will architect and productionise advanced regression and two-tower recommendation systems, using Bayesian methods and scalable pipelines.

You will work with tools like PyMC, Stan, and NumPyro, deploy via FastAPI and Docker, and lead experimentation including A/B testing and causal inference. This hybrid role combines research with production impact in a global mobility company.

Qualifications

• 5+ years of applied Bayesian methods in production systems.
• Fluent with PyMC, Stan, NumPyro, or TensorFlow Probability.
• Experience with large-scale recommender or pricing models is a plus.

Responsibilities

• Architect and prototype advanced regression models with Bayesian methods.
• Productionise personalization and recommendation systems at scale.
• Apply SVI, MCMC, and importance sampling for robust decisions.
• Build pipelines for feature engineering and data validation.
• Deploy models via FastAPI, Docker, or Kubeflow with monitoring.
• Design A/B tests and causal inference to measure value.

Skills

Bayesian modeling

Probabilistic models

PyMC

Stan

NumPyro

Two-tower models

MCMC

A/B testing

Docker

Tools

Docker

Kubernetes

FastAPI

Dagster

Airflow

Job description

SIXT is seeking a senior roles in Lisbon to develop probabilistic models guiding pricing and personalised offers. You will architect and productionise advanced regression and two-tower recommendation systems, using Bayesian methods and scalable pipelines.

You will work with tools like PyMC, Stan, and NumPyro, deploy via FastAPI and Docker, and lead experimentation including A/B testing and causal inference. This hybrid role combines research with production impact in a global mobility company.