Pinterest is looking to solve the business and technical problem of how advertisers understand the value of Pinterest by setting the vision and leading the science strategy behind ads measurement and attribution. This includes evolving approaches to be durable with cookie deprecation, ATT, SKAN, and cross-device fragmentation, while championing privacy-centric methodologies.
Requirements
- 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.
- Experience with ad platforms, retail media, or e-commerce measurement.
- Knowledge of identity resolution, SKAN/ATT, and browser privacy changes.
Responsibilities
- 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).
- 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.
- Evolve our multi-touch and data-driven attribution approaches to be durable with cookie deprecation, ATT, SKAN, and cross-device fragmentation.
Other
- 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.
- This role will need to be in the office for in-person collaboration 1-2 times/week in the San Francisco, Palo Alto, or Seattle offices.
