Description
You'll be part of our new Dynamic Pricing & Revenue Management team, working alongside a Data Analyst and Data Engineer. Together, you will work towards one core goal: helping hosts improve occupancy and earnings through a smart, dynamic and data driven pricing strategy.
You'll work with a large and rich dataset, modern tooling, and teammates who care deeply about impact, collaboration, and learning together. This role is based in Munich with 3 office days per week.
As a Senior Data Scientist, you'll take ownership of complex pricing and forecasting models and help us turn analytical ideas into real-world impact for hosts and Holidu. You will:
- Translate business questions into scientific, testable models and clear recommendations.
- Design, build and own machine learning, forecasting and predictive models for revenue management topics such as demand forecasting, price sensitivity, and conversion probability.
- Explore and develop dynamic pricing strategies (e.g. weekend pricing, early discounts, regional similarities) using data and experimentation.
- Collaborate closely with Data Analysts and Data Engineers to define datasets, features, and model requirements.
- Drive discussions around model choice, assumptions, and trade-offs, always keeping business impact in mind.
- Monitor model performance, iterate on results, and continuously improve accuracy and relevance.
- Act as a senior sparring partner in the team, sharing knowledge and raising the bar for data science practices.
You'll have 5+ years of experience as a Data Scientist, solving a variety of different business problems. You'll have a strong background in statistics, forecasting, and machine learning. You'll be hands-on with Python and SQL, and confident working with large datasets. You'll have a strong interest in pricing, revenue optimization, or marketplace dynamics (prior revenue management experience is a plus, not a must).
You'll be a self-starter: proactive, hungry to learn, and eager to make an impact. You'll be able to communicate complex ideas clearly and collaborate with technical and non-technical partners.