Director of Data Science, Ads Delivery & Performance

Pinterest Ads Delivery & Performance is redefining how digital ads are delivered - challenging 20 years of assumptions to both protect the Pinner experience and grow durable revenue. We support all ad surfaces across Pinterest - Home Feed, Search, Related Pins, Shopping surfaces, Idea Streams, and beyond - each with unique marketplace and product dynamics. You’ll lead a high‑impact data science organization that partners deeply with Product, Engineering, Research, and other cross functional partners to build the next generation of advertising products and systems.

About the role We’re looking for a Director who is a leader of leaders and a systems thinker. You will set the strategy for ads delivery and quality, establish the measurement and decision frameworks, and scale a best‑in‑class team of data scientists. A core mandate for this role is to identify, instrument, and operationalize the input metrics that most directly drive ads delivery, quality, and performance - ensuring we are optimizing the levers that move outcomes, not just reporting on lagging KPIs.

What you’ll do:

• Set strategy and outcomes
• Define the multi‑year vision and roadmap for Ads Delivery & Performance across all Pinterest surfaces, aligning to company and Ads org priorities.
• Establish clear north-star outcomes (e.g., long‑term revenue quality, retained advertiser value, Pinner experience) and the right cascade of input metrics and guardrails that drive them.
• Make input metrics a first‑class operating system
• Identify, define, and instrument the input metrics that most influence delivery and performance, such as: supply health and coverage, eligibility and match rate, win rate, fill rate, pacing and spend smoothness, auction/bid competitiveness, latency/SLA adherence, ranking/model freshness and coverage, feature quality, CTR/CVR leading indicators, frequency and ad load distribution, quality/relevance signals, and policy/trust frictions.
• Build metric specs, ownership, alerting, and weekly business reviews so that teams operate to inputs (and understand their elasticities to outcomes like RPM, ROAS, advertiser retention, and Pinner satisfaction).
• Lead an organization of leaders
• Hire, develop, and inspire a diverse, high‑performance organization of data science managers and senior ICs; set crisp role definitions, growth paths, and succession planning.
• Establish rigorous standards for experimentation, causal inference, and production analytics; ensure consistently trustworthy, decision‑grade outputs.
• Partner to ship impact
• Work hand‑in‑hand with Product and Engineering on marketplace, ranking, pacing, and quality systems (e.g., auction design, supply/demand balancing, relevance, cold‑start, ads load/frequency, shopping ads delivery).
• Translate ambiguous business questions into structured analyses and roadmaps; ensure the org moves from insight to shipped change with measurable impact.
• Elevate measurement and decision quality
• Own the measurement strategy for ads quality and delivery: counterfactual measurement, lift and incrementality, experiment design, long‑term value, and guardrail monitoring for Pinner experience.
• Improve our decision frameworks, define minimum statistical standards, and drive consistency in A/B testing, quasi‑experiments, and observational methods when experiments are impractical.
• Communicate and align
• Present complex analytical findings to executives and cross‑functional partners with clarity; drive alignment on trade‑offs across revenue, advertiser value, and Pinner experience.
• Create transparent operating cadences (QBRs/MBRs, input metric reviews, launch reviews) that keep teams focused on the levers that matter.

What we’re looking for:

• MS or PhD in a quantitative field (Computer Science, Statistics, Math, Engineering, Economics or related) or equivalent practical experience.
• 10+ years in Data Science, Algorithmic Engineering, or Machine Learning, with significant impact in digital advertising or large‑scale marketplaces.
• 5+ years directly managing data science organizations, including managing managers and scaling multi‑team groups in a technology company.
• Deep experience with:
• Statistical analysis and causal inference, experiment design, and measurement for complex marketplaces.
• Production analytics and large‑scale data tooling (e.g., Python/R, SQL; Spark/Hive or similar).
• Applied ML or relevance/ranking systems; familiarity with auction dynamics, pacing, bidding, and quality/relevance modeling.
• Proven track record of establishing and operating through input metrics tied to business outcomes.
• Excellent written and verbal communication; adept at influencing senior cross‑functional partners and executives.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
• This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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