Senior Data Science - Dynamic Pricing & Revenue Management

We're building Holidu's Dynamic Pricing & Revenue Management team from the ground up, and we're looking for a skilled and driven founding Senior Data Scientist.

You'll define the machine learning models and data science strategy behind how we price tens of thousands of holiday homes — working within a dedicated, cross-functional Revenue Management team.

The shared goal: help hosts improve occupancy and earnings through smart, dynamic, data-driven pricing, with machine learning at its core. You'll work with a large and rich dataset, fast paths from concept to production, and the autonomy to act on your own judgment.

Holidu is an AI-first company , and it shows in how we work: your modelling stays grounded in machine learning and statistics, but you'll have large-scale access to the best AI tools and the freedom to weave them into everything you do — from discovery to implementation to maintenance.

Everyone here experiments and shares what works, and we'll count on you to help push us to stay at the cutting edge . This role is based in Munich with a hybrid setup. Our Tech Stack Python

• Airflow

• dbt

• AWS (SageMaker, Redshift, Athena)

• MLflow Your role in this journey You'll own pricing and forecasting models at Holidu end-to-end — from first prototype to production systems that move real revenue. You will: Design, build, and own predictive models for demand, price sensitivity, and conversion probability.

Translate business questions into scientific, testable approaches and clear, actionable recommendations. Explore and develop dynamic pricing strategies (e. g. weekend pricing, early-bird discounts, regional similarities) through data and experimentation.

Run experiments in production , monitor performance, and iterate to keep accuracy and relevance high. Own the calls on model choice, assumptions, and trade-offs — you'll be the technical reference point for the team. Collaborate closely with Data Analysts and Data Engineers to define datasets, features, and model re