Director of Data Science, Ads Measurement & Attribution

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible.

As the Director of Data Science for Ads Measurement & Attribution, you will set the vision and lead the science strategy behind how advertisers understand the value of Pinterest. You'll own the roadmap for causal measurement, attribution, and incrementality-spanning first- and third-party solutions, experiment design (including incrementality studies), and model innovation that is privacy-safe and aligned with evolving industry standards. You'll grow and lead a high-performing team of data scientists and analysts, partner tightly with Eng and Product, and represent Pinterest science externally with customers and the ecosystem.

What you'll do:

• Vision and strategy
• Define and drive the end-to-end science strategy for ads measurement and attribution across on-platform, off-platform, and partner surfaces.
• Establish a coherent framework that integrates incrementality testing, causal inference, calibrated attribution, MMM, and geo experimentation.
• Champion privacy-centric methodologies (e.g., clean rooms, aggregation, differential privacy, conversion modeling under signal loss).
• Causal measurement and experimentation
• Lead the design and governance of lift studies where merchants run A/B tests to estimate lift and guide investment decisions.
• Build standardized experiment design patterns, power calculators, guardrails, and experiment-quality diagnostics.
• Develop causal estimators (e.g., CUPED, DR/DML, synthetic controls) and variance reduction techniques to improve sensitivity and speed to signal.
• Attribution and modeling
• Evolve our multi-touch and data-driven attribution approaches to be durable with cookie deprecation, ATT, SKAN, and cross-device fragmentation.
• Partner with Eng to product ionize calibrated models that reconcile observational and experimental evidence; define success metrics and calibration protocols.
• Advance conversion modeling, identity-resilient matching, and probabilistic methods where deterministic signals are sparse.
• Product and cross-functional leadership
• Partner with Product and Engineering to shape the measurement product roadmap; translate science into advertiser-facing solutions and clear narratives.
• Collaborate with Sales, Marketing Science, and Partnerships to position our methods with advertisers and measurement partners.
• Engage with Legal/Privacy to ensure compliance and responsible AI practices across data usage and modeling.
• Team building and talent development
• Hire, lead, and mentor a diverse team of DS managers and senior ICs; foster a culture of scientific rigor, reproducibility, and impact.
• Set standards for code quality, experimentation hygiene, documentation, and peer review across the DS org.
• Influence and external representation
• Represent Pinterest science in customer briefings, industry forums, and with third-party measurement partners and clean-room providers.
• Contribute to publications, whitepapers, and internal tech talks that raise the scientific bar.

What we're looking for:

• Leadership and experience
• 10+ years of experience in data science, statistics, or applied ML, with substantial time in ads measurement, attribution, or experimentation at scale.
• 5+ years leading DS teams, including managing managers and senior ICs; proven track record of building high-performing, inclusive teams.
• Demonstrated success driving cross-functional impact with Product, Engineering, Sales, and Legal/Privacy.
• Exceptional communication skills-able to explain complex methods to executives and customers and to translate business needs into scientific work.
• Technical and methodological depth
• Strong foundation in causal inference and experimentation (A/B testing, geo experiments, quasi-experimental designs, variance reduction).
• Hands-on experience with attribution and calibration (rule-based and data-driven MTA, counterfactual estimation, aggregation and identity challenges).
• Familiarity with MMM and triangulation approaches that reconcile MMM, MTA, and lift tests.
• Proficiency in Python or R; strong SQL; comfort reviewing production code and collaborating with platform/ML engineers.
• Experience with privacy-centric measurement: clean rooms, aggregation frameworks, differential privacy, on-device/edge signals, and privacy regulations.
• Product mindset
• Evidence of turning science into durable, scalable products with clear customer value.
• Fluency in metric design, north-star definitions, and guardrails that align with advertiser outcomes.

• Experience with ad platforms, retail media, or…