Vice President, Data Science & Product Analytics

Vice President, Data Science & Product Analytics

Who We Are

At ad Marketplace, our mission is to deliver the most engaging consumer search experiences while empowering advertisers to measure media performance accurately. Today, millions of people worldwide engage with our exclusive, transparent media placements across the internet’s leading browsers, shopping apps, and review sites.

Our award-winning culture is built around five core values (known as our 5C’s):
Curiosity, Collaboration, Creative Conflict, Commitment, and Competitiveness. With these guiding values, ad Marketplace seeks to empower our team to reach their full potential through continued learning, and the opportunity to do their best work.

About Ad Marketplace

ad Marketplace operates the largest search advertising marketplace outside traditional search engines, enabling advertisers to reach high-intent consumers across the open web. Our platform is built on real-time auctions, performance optimization, and rigorous measurement—where understanding why things happen is just as important as what happens.

Role Overview

The Vice President, Data Science & Product Analytics is responsible for putting data at the center of great product and business decision-making s person will drive a culture of proactive insight generation—where the team finds issues before they become problems and identifies optimization levers. You will also partner closely with Product, Engineering, and Commercial teams to ensure insights translate into measurable product outcomes.

This Person Will Own

• 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, surfaces opportunities, and influences 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

Problem Discovery & Strategic Opportunity Identification

• Actively surface previously unknown risks and opportunities
• Identify leading indicators of performance degradation or growth potential.
• Influence product strategy by connecting analytical findings directly to business impact, trade-offs, and expected outcomes.
• Guide product teams toward the highest-leverage opportunities using data-backed narratives

Experimentation, Causal Measurement & Analytics

• 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.
• 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

• Product direction
• Marketplace policies
• Pricing and monetization decisions
• Prepare and deliver clear, compelling narratives that connect product behavior to business outcomes

Required Skills & Experience

• Deep expertise in product analytics and experimentation, including A/B and multivariate testing, incrementality and lift analysis, funnel and cohort analysis, and KPI forecasting
• Strong statistical foundation with the ability to interpret complex experimental and causal results
• Advanced SQL skills and experience working with large, event-level datasets; fluency with modern analytics, data platforms, and visualization tools (e.g., Tableau,…