Director, Applied Science and Product Analytics

Who We Are
adMarketplace is the largest global marketplace for Native Search advertising. For over 25 years, we’ve connected brands with consumers at the moment they express commercial intent beyond legacy search engines.

Today, our Native Search solutions are exclusively integrated across next-generation platforms where discovery happens, including web browsers, Buy Now Pay Later apps, and AI chat surfaces. Powered by vector search technology, our platform delivers relevant text and product ads that match consumers with the brands, products, and offers they’re actively seeking.

Our award-winning culture is grounded in the principles of Curiosity, Collaboration, Creative Conflict, Commitment, and Competitiveness – our 5Cs. These values drive us to turn complexity into clarity and create measurable value for consumers, advertisers, and publishers alike.

The Role
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.

What You’ll 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, 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

Required Skills & Experience

Hands‑on applied science or data science background — you should be as comfortable building models and writing production SQL as you are leading a team

Experience owning a measurement function including attribution, incrementality, ad effectiveness, or campaign measurement with a track record of building trusted, scalable measurement infrastructure

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 the 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 (e.g., Databricks, BigQuery, Snowflake) and visualization tools (e.g., Tableau)

Experience working in adtech, search advertising, or performance marketing is required with direct exposure to auction mechanics, ranking systems, bid optimization, or marketplace analytics strongly preferred

Strong product and business intuition, with a 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 deeply 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; you won’t walk into clean, well‑structured data and should have experience diagnosing data quality issues and building toward reliable infrastructure

Join Us
adMarketplace has been named as one of the best places to work in New York City by Built In and Crain’s- the latter of which have recognized us the past three years straight! AMP is currently experiencing triple digit growth, and it’s never been a better time to join our team!

We offer a robust continuing education program, management training, regular company‑wide lunch and learns, and well‑defined career paths to ensure all our employees have an opportunity to grow.

At adMarketplace, we play to win, but we learn from our setbacks. Our commitment to a collaborative environment means no one succeeds alone, and no one fails alone either.

We know you’ve come to expect comprehensive healthcare, wellness programs, paid time off, commuter benefits, and 401k matching from any company, so it’s a good thing we offer all of that and so much more. adMarketplace offers Summer Fridays, catered lunches, a fully stocked kitchen, ZogSports teams, happy hours and corporate retreats to encourage a strong work/life balance.

*This range represents the low and high end of the base salary someone in this role may earn as an employee of adMarketplace in the New York office. Salaries will vary based on various factors including but not limited to professional and academic experience; training; associated responsibilities; and other business and organizational needs. The range listed is just one component of our total compensation package for employees. Salary decisions are dependent on the circumstances of each hire.

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