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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.
Job Responsibility:
Proactively identify high-impact business problems and define the analytical strategy to solve them, moving work forward autonomously
Deliver impactful insights that move key OKRs and business KPIs rather than focusing solely on task-based output
Communicate insights in the context of business outcomes, unblocking decisions for your productuser groups through clear, concise narratives
Design, execute, and analyze complex experiments, accounting for network effects and high variance in a two-sided marketplace
Partner with Product + Engineering to define app analytical events and schema requirements, ensuring data integrity is built-in at the point of collection
Ensure all work is reproducible, scalable, and verifiable
Conduct peer reviews and raise the technical bar for the team
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
Synthesize complex data signals into Product and Engineering Requirement Documents (PRDs/ERDs) that provide clear, executable direction for senior leadership and stakeholders
Leverage AI-assisted coding and analysis tools to optimize workflows in the role
Evangelize emerging technology trends and evaluate how AI tools can be integrated to reduce technical debt and/or improve team procedures
Requirements:
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)
Expert proficiency in SQL and Python/R, specifically for the purpose of building scalable, flexible, and reproducible analytical frameworks
Proven ability to identify, frame, and solve complex business problems from scratch without requiring constant managerial guidance
Experience designing and executing complex A/B or switchback experiments, including a deep understanding of statistical power and variance reduction
History of contributing to technical documents (PRDs, ERDs, or white papers) that translate data into executable product strategy
Nice to have:
Prior experience in the Payments industry, specifically regarding user facing products and/or payout systems or ledger management
Familiarity with internal experimentation platforms and/or high-scale data infrastructure
Experience managing distributed stakeholders and the ability to manage a high volume of requests independently
Experience building or maintaining data pipelines to ensure long-term data health and reporting sustainability
Demonstrated use of AI-assisted tools to automate routine validation, data monitoring, and analysis workflows