Staff Data Scientist, Growth Data Products
GetYourGuide · 🌍 Berlin
Sponsorship verdict
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No government record and no wording either way. Not a refusal — ask the recruiter.
- No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
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Sponsor Radar — GetYourGuide
This employer posted directly and does not match a government sponsor register.
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About the role
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. • Champion a culture of experimentation through A/B test design, causal-inference analysis, and frameworks for rapid iteration. • Advance customer lifetime value and attribution models that guide multi-million euro marketing investments. • Drive cross-functional collaboration to ensure data products deliver tangible business value and strategic impact. Your toolkit • Proven track record as a Staff or Principal Data Scientist (or equivalent) delivering cross-functional products that deliver significant business value. • Market and growth experience is essential, with strong domain knowledge in marketing analytics, customer acquisition, or revenue optimization. • Mastery of Python, SQL, and modern big-data tools such as Spark and Databricks, with comfort in shipping production-grade machine learning services. • Deep expertise in statistical testing, causal inference, and online experimentation frameworks. • Hands-on experience in marketing growth areas like paid search, CRM, or attribution modeling. • Advanced degree in a quantitative field (such as Statistics, Computer Science, Mathematics, Economics, or Physics) or equivalent practical experience. • Strong communication skills that enable you to influence both technical and non-technical audiences across the organization. Extras that give you an edge • Experience with cloud orchestration and CI/CD technologies such as AWS, Airflow, or Kubernetes. • Familiarity with Snowflake, MLflow, or large-scale feature-store architectures. • A record of mentoring senior individual contributors and fostering a culture of psychological safety across teams. • Publications or conference presentations on topics like large language models, agentic AI systems, or marketing technology innovation. How we’ll make your career journey extraordinary • Annual personal growth budget and mentorship programs for continuous learning and development • Work from anywhere in the world for 30 days per year • A hybrid working approach with three days of in-office collaboration (Mon, Tue, Thur) and two days of optional at