Product Data Scientist
UberAmsterdam, NetherlandsPosted 19 March 2026
Tech Stack
Job Description
Product Data Scientist
Department: Data Science
Team: Data Scientist
Location: Amsterdam, Netherlands
Type: Full-Time
**About the Role**
We are seeking a **Data Scientist II** to join the Payments Data Science in Amsterdam. This project lead role will specifically support a product within the **Earner Payments Portfolio** and this is a global role. You will act as a strategic partner to product and engineering teams to shape the product roadmap and drive data-informed decisions.
**Note on Scope:** This role focuses on product analytics, experiment design, stakeholder management and strategic synthesis. If your primary interest is in developing production-level ML models, please refer to Applied Science openings.
**What You Will Do**
01. **Strategic Roadmap Ownership:** Proactively identify high-impact business problems and define the analytical strategy to solve them, moving work forward autonomously.
02. **Outcome-Driven Analysis:** Deliver impactful insights that move key OKRs and business KPIs rather than focusing solely on task-based output.
03. You are expected to communicate insights in the context of business outcomes, unblocking decisions for your productuser groups through clear, concise narratives.
04. **Full Lifecycle Experimentation:** Design, execute, and analyze complex experiments, accounting for network effects and high variance in a two-sided marketplace.
05. **Instrumentation & Technical Rigor:** Partner with Product + Engineering to define app analytical events and schema requirements, ensuring data integrity is built-in at the point of collection.
06. **Technical Leadership:** Ensure all work is reproducible, scalable, and verifiable. You will be expected to conduct peer reviews and raise the technical bar for the team.
07. **Stakeholder Influence:** Independently manage and influence cross-functional roadmaps by providing practical, well-thought-out recommendations that reflect a clear understanding of the "why" behind the data.
08. Synthesize complex data signals into Product and Engineering Requirement Documents (PRDs/ERDs) that provide clear, executable
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