Staff Data Scientist, Growth Data Products
GetYourGuide - Berlin
Posted Mar 27, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Assessment
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- Deadline
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Where they hire
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About this role
Staff Data Scientist, Growth Data Products Berlin 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 Growth Data Products (GDP) drives GetYourGuide's growth engine by transforming raw marketing data into reliable, self-service insights and automated decision systems. Our work spans every growth channel-Paid and Organic Search, Display Advertising, CRM and Lifecycle Marketing, Brand Marketing, Marketing Attribution, Experimentation, and Customer Lifetime Value measurement. We empower teams across the organization to make faster, smarter decisions at scale, turning data into actionable intelligence that fuels our mission to connect millions with unforgettable travel experiences. Your mission - Define, develop, and fully own data products that drive measurable revenue impact across all GDP domains. - Translate growth strategies into technical roadmaps, aligning multiple squads and stakeholders around clear, measurable business outcomes. - Design, deploy, and monitor production machine learning pipelines in Python and Databricks to support bidding, targeting, and personalization use cases. - Raise the technical standard by introducing best practices, code quality standards, and robust observability within the data science and engineering teams.
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