Responsibilities

• Demand Health & Measurement
• - Define the North Star metrics, diagnostic framework, and measurement strategy for demand health across the ads system.
• - Build the operating view of demand across spend, active advertisers, retention, budget utilization, delivery, concentration, and mix; identify emerging risks and opportunities.
• - Diagnose changes in demand through cohort analysis, decomposition, experimentation, and causal methods, translating findings into clear actions for Sales and Product leadership.
• Advertiser Performance & Benchmarks
• - Own the end-to-end view of advertiser outcomes—including delivery, ROAS, conversion performance, retention, and budget efficiency—for individual advertisers and key cohorts.
• - Establish actionable benchmarks by objective, vertical, advertiser size, geography, maturity, and product adoption, with statistically sound peer comparisons.
• - Develop early-warning signals and opportunity scoring that help sales teams surface under-delivery, performance risk, and advertiser growth potential.
• - Set standards for metric definitions, data quality, and interpretation so leaders can separate real marketplace changes from seasonality, selection effects, and measurement artifacts.
• Insights, Adoption & Advertiser Feedback

Requirements

• 7+ years of experience in data science or analytics within an ads platform, marketplace, or performance-oriented B2B business.
• Demonstrated business impact through advertiser demand growth, improved delivery or ROAS, stronger retention, or decisions that changed product and sales strategy.
• Strong SQL and Python or R, with depth in measurement, experimentation, causal inference, segmentation, benchmarking, and forecasting.
• Exceptional cross-functional communication and influence with both sales and product leaders, plus a hands-on approach to ambiguous, 0-to-1 problems.

Preferred

• Experience at a high-performing ads business where data scientists work broadly across Sales, Marketing Science, and Product rather than in a narrow silo.
• Hands-on familiarity with ad delivery, auctions, measurement, attribution, conversion signals, and the advertiser lifecycle.
• Experience turning customer feedback into product priorities and evidence-backed best practices that improve advertiser outcomes.