Decision Scientist

Change the way the world travels

Join the GetYourGuide journey to connect people with unforgettable travel experiences around the world. Millions look to us for unique activities they can trust, and it’s all powered by our commitment to make every single journey extraordinary - including yours. 

Ready to unlock your potential with a community of fellow explorers? Find your next role at our Berlin HQ or one of our local offices around the globe, from New York to Bangkok. Head to getyourguide.careers to take the first step.

Team mission

This specific position sits within our Growth Analytics team, whose objective is to scale marketing investment toward the most incremental and loyal customers. The role is focused on our paid search channel where black-box auction dynamics, branded vs non-branded incrementality, and elasticity modelling define the analytical problem. The successful candidate will also contribute to cross-channel measurement questions as they arise.

Your mission

• Develop quantitative analysis and statistical models to evaluate and steer marketing decisions
• Propose and defend strategic recommendations to our top marketing leads
• Setup and analyse marketing experiments to drive strategic decision making
• Explore large datasets, give meaning to data and numbers, identify opportunities and issues, and present findings to stakeholders
• Maintain and improve our marketing measurement tools (Attribution, experimentation framework, Customer lifetime value…)
• Serve as a liaison between the marketing teams and the data engineering team
• Mentor others in the skills needed for this role
• Use AI to accelerate end-to-end analysis — from framing the question to delivering the insight — while holding a high bar for methodological rigor and validation

Your toolkit

• 8+ years of relevant experience interpreting data in an analytics or data science role
• Prior experience analysing paid search and/or SEO performance, using platforms such as Google Ads/Search.
• Strong knowledge of SQL and Python for analysis (eg, pandas, scikit-learn, pyspark)
• Hands-on experience with causal inference methods (e.g. geo experiments, difference-in-differences, synthetic controls) and/or elasticity modelling applied to marketing spend decisions.
• Ability to understand user behavior and meaning behind the numbers and a track record in sharing insights to business stakeholders.