Product Data Scientist

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

1. Strategic Roadmap Ownership: Proactively identify high-impact business problems and define the analytical strategy to solve them, moving work forward autonomously.
2. Outcome-Driven Analysis: Deliver impactful insights that move key OKRs and business KPIs rather than focusing solely on task-based output.
3. You are expected to communicate insights in the context of business outcomes, unblocking decisions for your productuser groups through clear, concise narratives.
4. Full Lifecycle Experimentation: Design, execute, and analyze complex experiments, accounting for network effects and high variance in a two-sided marketplace.
5. 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.
6. 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.
7. 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.
8. Synthesize complex data signals into Product and Engineering Requirement Documents (PRDs/ERDs) that provide clear, executable direction for senior leadership and stakeholders.
9. AI & Technical Innovation: Leverage AI-assisted coding and analysis tools to optimize workflows in the role.
10. Evangelize emerging technology trends and evaluate how AI tools can be integrated to reduce technical debt and/or improve team procedures.

What You Will Need

Basic Qualifications

1. Education & Experience: Bachelor’s with 5+ years, Master’s with 3–5+ years in a quantitative field (e.g., Statistics, Applied Math, CS, Operations Research, or Physics).
2. Technical Mastery: Expert proficiency in SQL and Python/R, specifically for the purpose of building scalable, flexible, and reproducible analytical frameworks.
3. Autonomous Problem Discovery: Proven ability to identify, frame, and solve complex business problems from scratch without requiring constant managerial guidance.
4. Experimental Design: Experience designing and executing complex A/B or switchback experiments, including a deep understanding of statistical power and variance reduction.
5. Documentation: History of contributing to technical documents (PRDs, ERDs, or white papers) that translate data into executable product strategy.

Preferred Qualifications

1. Industry Context: Prior experience in the Payments industry, specifically regarding user facing products and/or payout systems or ledger management.
2. Platform Knowledge: Familiarity with internal experimentation platforms and/or high-scale data infrastructure.
3. Operational Influence: Experience managing distributed stakeholders and the ability to manage a high volume of requests independently.
4. Data Engineering: Experience building or maintaining data pipelines to ensure long-term data health and reporting sustainability.
5. AI Experience: Demonstrated use of AI-assisted tools to automate routine validation, data monitoring, and analysis workflows

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuelds progress. What moves us, moves the world - let’s move it forward, together.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.