Director, Applied Science and Product Analytics

What you'll do

• Product analytics and performance diagnostics across the marketplace
• Deep-dive investigations into auction outcomes, click & conversion funnels, supply quality, advertiser ROI, financial analysis, user behavior, and ranking logic
• Develop frameworks to surface hidden performance issues, inefficiencies, and optimization opportunities
• Identify problems, surface opportunities, and influence product direction partnering with Product, Engineering, Design, FP&A, and Commercial leadership
• Product health measurement, opportunity discovery, and forecasting
• Provide executive-facing insights that shape roadmap priorities and investment decisions
• Diagnose performance issues across auctions, ranking and relevance, and conversion funnels
• Analyze supply–demand dynamics and marketplace balance
• Evaluate performance by advertiser, query, geo, device, and vertical segments
• Translate complex data into clear, prioritized problem statements for product teams
• Inherit and improve a complex, unstructured data environment by diagnosing data quality issues, establishing standards, and building a clean, reliable foundation for measurement and decision-making
• Own experimentation, causal inference, and incrementality frameworks to ensure decisions are grounded in validated impact
• Partner with Product, Engineering, and Data Engineering to design, run, and interpret experiments evaluating features, ranking changes, and marketplace policies
• Apply applied science methodologies including causal inference, propensity modeling, and quasi-experimental design to marketplace and product problems
• Standardize measurement, metrics, and reporting across product teams
• Build scalable analytics and experimentation systems delivering fast, trusted insights from complex event-level data
• Prepare and deliver clear, compelling narratives connecting product behavior to business outcomes
• Inform product direction, marketplace policies, and pricing and monetization decisions with rigorous, data-backed analysis
• Serve as the analytical voice in executive conversations, translating complex findings into prioritized, actionable recommendations
• Own advertiser and campaign measurement frameworks including attribution, incrementality, and ad effectiveness methodology
• Lead the BI function including BI engineers, reporting infrastructure, and self-service analytics capabilities
• Define and enforce data quality standards, measurement best practices, and metric governance across product and commercial teams
• Build and maintain a single source of truth for marketplace KPIs
• Own the measurement roadmap identifying and closing gaps in performance measurement
• Partner with Data Engineering to ensure data infrastructure supports fast, reliable, and scalable measurement and reporting

Requirements

• Hands-on applied science or data science background
• Experience owning a measurement function including attribution, incrementality, ad effectiveness, or campaign measurement
• Experience leading or overseeing a BI function including data products, reporting infrastructure, and self-service analytics
• Deep expertise in product analytics and experimentation including A/B and multivariate testing, incrementality and lift analysis, causal inference, funnel and cohort analysis, and KPI forecasting
• Strong statistical foundation with ability to design, execute, and interpret complex experimental and causal results
• Advanced SQL skills and experience working with large, event-level datasets
• Fluency with modern analytics and data platforms (Databricks, BigQuery, Snowflake) and visualization tools (Tableau)
• Experience working in adtech, search advertising, or performance marketing
• Direct exposure to auction mechanics, ranking systems, bid optimization, or marketplace analytics preferred
• Strong product and business intuition with track record of influencing product strategy and connecting insights to growth, efficiency, and P&L impact
• Demonstrated ability to lead and develop analytical teams while remaining hands-on
• Ability to clearly communicate complex insights to executive audiences
• Degree in a quantitative field (Statistics, Economics, Mathematics, Computer Science, or similar); advanced degree a plus
• 8–12+ years of experience in applied science, data science, product analytics, experimentation, and/or performance measurement
• Comfort operating in and improving messy data environments; experience diagnosing data quality issues and building toward reliable infrastructure

Tech stack

Benefits