We are looking for a Staff Data Scientist, Data Products to serve as a senior analytical and product partner across Syndio's product and data-product portfolio. You will own measurement strategies for our product platform, translate usage and business data into product decisions, and help turn those signals — together with pay-equity, policy, job architecture, market, and workforce data — into customer-facing analytical products.

This is a high-autonomy, high-visibility staff role. You will lead ambiguous, cross-functional work from opportunity discovery through methodology, validation, production, and launch; partner with Product, Data Science, Engineering, Privacy, Legal, Sales, and Customer Success; and set standards for analytical rigor, interpretability, data quality, and responsible data use. The role is an individual contributor position with broad influence.

Product Measurement & Decision Support

• Own measurement strategies for Syndi's core user workflows — including offer endorsement, approval, and acceptance — defining events, metrics, and success criteria that guide product decisions.
• Partner with engineering to design and validate event instrumentation for new features, ensuring tracking is accurate, consistent, and privacy-safe from the start.
• Conduct deep-dive analyses into feature adoption, workflow completion, user engagement, customer outcomes, and operational patterns to surface actionable insights.
• Build and maintain production-grade dashboards and self-serve reporting in Mixpanel, BigQuery, and BI tooling that give product teams and senior leaders visibility into product health.
• Translate complex, ambiguous usage data into clear, prioritized recommendations for technical, product, and executive audiences.

Data Product Development

• Define and lead analytical strategies for new compensation and workforce data products that make Syndio more valuable, differentiated, and difficult to replicate.
• Identify high-value opportunities to combine Syndio's aggregated and anonymized first-party data with compensation market data, job-posting and skills data, and other third-party sources.
• Develop diagnostics that measure compensation governance and execution health, including policy-versus-practice gaps, job-architecture health, governance adoption, strategic alignment, and overpayment risk.
• Lead complex initiatives from early exploration and hypothesis formation through analytical validation, productionization, commercialization, and launch.
• Evaluate whether proposed data products are analytically defensible, interpretable, commercially valuable, privacy-preserving, and responsible to use.
• Contribute to the give-to-get data strategy by identifying which product and customer signals can strengthen Syndio's broader data assets over time.

Cross-functional Leadership & Standards

• 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 data-product insights to customer value, health, and renewal risk.
• Establish and champion standards for event data, analytical quality, documentation, interpretability, privacy, and responsible data use.
• Provide technical and analytical leadership to other practitioners, raise data literacy across the product organization, and build self-serve capability.

• 8+ years of experience in product analytics, data science, analytics engineering, or a closely related role, including substantial experience supporting software products and/or developing analytical products.
• Proficiency with AI-assisted development tools and workflows, using them to accelerate analysis, prototyping, code generation, documentation, and data-product development while validating outputs and exercising sound judgment.
• Familiarity with emerging AI and BI innovation — including natural-language interfaces, automated insights, semantic layers, and agentic workflows — and the ability to evaluate where these capabilities can improve analytical products and customer experiences.
• A track record of setting direction and leading complex, cross-functional initiatives with significant product or business impact.
• Deep proficiency in SQL and strong working proficiency with Python, R, or a comparable analytical language.
• Advanced knowledge 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-serve reporting using tools such as Mixpanel, Amplitude, Looker, Tableau, or equivalent.
• Experience combining large, imperfect datasets into analytically defensible, interpretable, and commercially valuable products or insights.
• Exceptional judgment and comfort operating in ambiguous, evolving problem spaces; able to determine when approximation is appropriate and when precision is required.
• Ability to influence senior stakeholders, communicate complex methodologies clearly, and drive alignment across technical and non-technical audiences.

Extra Credit

• Experience instrumenting or evaluating a GenAI-native product, including model-assisted workflows.
• Deep familiarity with compensation, pay equity, workforce planning, labor-market data, job architecture, skills taxonomies, or people analytics.
• Experience with compensation surveys, job-posting data, privacy-preserving analytics, or third-party data licensing and governance.
• Familiarity with GDPR/CCPA and related privacy considerations for user-level event data and aggregated or anonymized customer data.