Staff Data Scientist, Data Products

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.

Accountabilities:

• 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, interpretability, commercial value, privacy preservation, and responsible use.
• Contribute to data strategy by identifying product and customer signals that can strengthen broader data assets over time.
• Serve as a senior analytical partner in product discovery, sprint planning, roadmap discussions, business reviews, and product planning cycles.
• Partner with Data Science on experiment design, causal analysis, model evaluation, and measurement of model-assisted workflows.
• Work with Customer Success and Sales to connect product usage and analytical insights to customer value, account health, and renewal risk.
• Establish and champion standards for event data, analytical quality, documentation, interpretability, privacy, and responsible data practices.
• Provide technical and analytical guidance to other practitioners, strengthen data literacy across the product organization, and enable greater self-service analytical capability.

Requirements:

• 8+ years of experience in product analytics, data science, analytics engineering, or a closely related discipline, including significant experience supporting software products or developing analytical products.
• Experience using AI-assisted development tools and workflows to accelerate analysis, prototyping, coding, documentation, and data-product development while independently validating outputs and applying sound judgment.
• Familiarity with emerging AI and BI capabilities such as natural-language interfaces, automated insights, semantic layers, and agentic workflows, with the ability to assess how these technologies can improve analytical products and customer experiences.
• Demonstrated track record of setting direction and leading complex, cross-functional initiatives with meaningful product or business impact.
• Deep proficiency in SQL and strong working knowledge of Python, R, or a comparable analytical programming language.
• Advanced understanding of statistical measurement, benchmarking, experimentation, data modeling, segmentation, data quality assessment, and analytical validation.
• Experience designing event schemas, product measurement strategies, funnels, dashboards, and self-service reporting using tools such as Mixpanel, Amplitude, Looker, Tableau, or equivalent platforms.
• Proven ability to combine large, complex, and imperfect datasets into analytically defensible, interpretable, and commercially valuable products or insights.
• Exceptional analytical judgment and comfort operating in ambiguous and evolving problem spaces, including the ability to determine when approximation is appropriate and when precision is essential.
• Strong stakeholder management and communication skills, with the ability to explain complex methodologies clearly and influence both technical and non-technical audiences.
• Experience instrumenting or evaluating GenAI-native products and model-assisted workflows is a strong plus.
• Familiarity with compensation, pay equity, workforce planning, labor-market data, job architecture, skills taxonomies, or people analytics is advantageous.
• Experience with compensation surveys, job-posting data, privacy-preserving analytics, or third-party data licensing and governance is a plus.
• Familiarity with GDPR, CCPA, and related privacy considerations for user-level event data and aggregated or anonymized customer data is desirable.

Benefits:

• Annual salary range of $180,000-$205,000 USD.
• Geo-neutral U.S. compensation approach based on job function and level rather than location.
• Equity participation to share in the organization’s success.
• Flexible vacation policy designed to support time away and recharging.
• Paid sick and safe time, compassion leave, and voting leave.
• Paid parental leave.
• Medical, dental, and vision coverage, with 90% of employee premiums and 50% of dependent premiums covered.
• Employer-paid life insurance and disability coverage.
• 401(k) retirement savings plan.
• Fully remote work model within the United States.
• Opportunity to work on innovative data products and analytical solutions with significant product and business impact.
• Collaborative environment that values candor, curiosity, community, learning, and diverse perspectives.