Director of Applied Science and Product Analytics

The Director, Applied Science & Product Analytics is responsible for putting data at the center of great product and business decision-making at adMarketplace
This is a highly hands-on, technically deep role
We are looking for someone who is as comfortable writing SQL and building causal inference frameworks as they are presenting findings to executive leadership
This person will drive a culture of proactive insight generation where the team finds issues before they become problems and identifies optimization levers
You will partner closely with Product, Engineering, and Commercial teams to ensure insights translate into measurable product outcomes
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
Developing frameworks to surface hidden performance issues, inefficiencies, and optimization opportunities
Identifying problems, surfacing opportunities, and influencing product direction — partnering closely with Product, Engineering, Design, FP&A, and Commercial leadership
Product health measurement, opportunity discovery, and forecasting
Executive-facing insights that shape roadmap priorities and investment decisions
Diagnosing performance issues across auctions, ranking and relevance, and conversion funnels
Analyzing supply–demand dynamics and marketplace balance
Evaluating performance by advertiser, query, geo, device, and vertical segments
Translating complex data into clear, prioritized problem statements for product teams
Inherit and improve a complex, unstructured data environment — diagnosing data quality issues, establishing standards, and building toward a clean, reliable foundation for measurement and decision-making
Experimentation, Causal Measurement & Applied Science:
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 that deliver fast, trusted insights from complex event-level data and directly inform roadmap and investment decisions
Executive Storytelling & Decision Support:
Prepare and deliver clear, compelling narratives that connect 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
Measurement & BI Ownership:
Own advertiser and campaign measurement frameworks including attribution, incrementality, and ad effectiveness methodology, ensuring advertisers and internal stakeholders have trusted, rigorous measurement of performance
Lead the BI function, including BI engineers, reporting infrastructure, and self-service analytics capabilities across the organization
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, ensuring consistent, trusted data products are available to Product, Engineering, FP&A, and Commercial leadership
Own the measurement roadmap identifying gaps in how performance is measured and systematically closing them
Partner with Data Engineering to ensure the underlying data infrastructure supports fast, reliable, and scalable measurement and reporting
Benefits

Medical/Dental/Vision/FSA
Wellness Programs & Social Events
Life/Disability Insurance
Matching 401k
Employee Referral Bonus Program
Discounted Gym Membership
Tax-Free Commuter Benefits
Advanced SQL skills and experience working with large, event-level datasets; fluency with modern analytics and data platforms (e.g., Databricks, BigQuery, Snowflake) and visualization tools (e.g., Tableau)Comfort operating in and improving messy data environments; you won’t walk into clean, well-structured data and should have experience diagnosing data quality issues and building toward reliable infrastructureExperience owning a measurement function including attribution, incrementality, ad effectiveness, or campaign measurement with a track record of building trusted, scalable measurement infrastructureStrong product and business intuition, with a track record of influencing product strategy and connecting insights to growth, efficiency, and P&L impactExperience leading or overseeing a BI function, including data products, reporting infrastructure, and self-service analyticsDegree in a quantitative field (Statistics, Economics, Mathematics, Computer Science, or similar); advanced degree a plusExperience working in adtech, search advertising, or performance marketing is required with direct exposure to auction mechanics, ranking systems, bid optimization, or marketplace analytics strongly preferredAbility to clearly communicate complex insights to executive audiencesStrong statistical foundation with the ability to design, execute, and interpret complex experimental and causal results8–12+ years of experience in applied science, data science, product analytics, experimentation, and/or performance measurementDeep expertise in product analytics and experimentation, including A/B and multivariate testing, incrementality and lift analysis, causal inference, funnel and cohort analysis, and KPI forecastingDemonstrated ability to lead and develop analytical teams while remaining deeply hands-onHands-on applied science or data science background — you should be as comfortable building models and writing production SQL as you are leading a team
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