Staff Data Scientist, Data Products

About the role

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Scientist, Data Products based in the United States. The Staff Data Scientist, Data Products will serve as a senior analytical and product partner across a broad portfolio of software and data products. The role combines product analytics, data science, measurement strategy, and analytical product development to turn complex data into meaningful business and customer outcomes. You will lead high-impact initiatives from opportunity discovery and methodology design through validation, production, commercialization, and launch. Working with Product, Data Science, Engineering, Privacy, Legal, Sales, and Customer Success, you will influence decisions across the organization while operating with significant autonomy. You will also help shape responsible standards for data quality, interpretability, privacy, and analytical rigor. A major focus will be developing innovative data products using compensation, workforce, market, and other aggregated or anonymized data sources. This is a high-visibility individual contributor role with broad influence over product strategy, analytical practices, and the development of scalable data capabilities.

Responsibilities

• Own measurement strategies for core product workflows, defining events, metrics, success criteria, and analytical frameworks that guide product decisions.
• Partner with Engineering to design and validate event instrumentation for new features, ensuring tracking is accurate, consistent, reliable, and privacy-conscious from the outset.
• Conduct deep-dive analyses covering feature adoption, workflow completion, engagement, customer outcomes, and operational patterns to identify actionable opportunities.
• Build and maintain production-grade dashboards and self-service reporting using tools such as Mixpanel, BigQuery, and BI platforms to provide visibility into product performance and health.
• Translate complex and ambiguous usage data into clear, prioritized recommendations for technical teams, product leaders, and executives.
• Define and lead analytical strategies for new compensation and workforce data products that create differentiated customer value.
• Identify opportunities to combine aggregated and anonymized first-party data with compensation market information, job-posting and skills data, and other third-party sources.
• Develop analytical diagnostics that assess compensation governance and execution, including policy-versus-practice gaps, job architecture health, governance adoption, strategic alignment, and overpayment risk.
• Lead complex data-product initiatives from early exploration and hypothesis development through analytical validation, productionization, commercialization, and launch.
• Evaluate proposed data products for analytical defensibility, interpret