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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, specifically improving conversion ads performance and unlocking new optimization objectives through identity and conversion modeling

Requirements

• MS or PhD degree in Computer Science, Machine Learning, Statistics or related field
• 6+ years of industry experience with related background in Ads conversion modeling/products or Ads measurement modeling/science
• 2+ years of experience as TLM or EM managing an engineering or applied science team
• Strong software engineering and mathematical skills with knowledge of machine learning

Responsibilities

• Lead the roadmap and technical direction for User Match Prediction (UMP)—from features and training data to model deployment—to increase match rate/quality and strengthen downstream attribution and optimization
• Define and productionize a model to generate a user match confidence score, and use it to optimize label weighting and feature construction in conversion models (e.g., oCPM/ROAS)
• Develop and ship models that increase incremental conversions, partnering with Data Science and Product to set success criteria and measurement plans
• Partner with Ads Measurement, Ads Signals, Ranking, and ML Infra to translate identity improvements into reliable online impact and strong operational readiness
• Guide model architecture evolution (e.g., feature interactions, multi‑task learning, serving freshness) and iterate on UMP initiatives that expand coverage and resilience (CAPI, WAU attribution, IP‑loss mitigation)
• Contribute to the longer‑term Identity Graph (IDG) collaboration (multi‑hop identifiers, candidate generation and ranking) to improve identity resolution and downstream utility
• Hire, mentor and grow ML engineers in ads quality and partner teams and help to uplevel ML talent across the company

Other

• MS or PhD degree in Computer Science, Machine Learning, Statistics or related field
• 2+ years of experience as TLM or EM managing an engineering or applied science team
• In-office collaboration once a week, commutable distance from San Francisco / Palo Alto / Seattle offices
• US based applicants only
• Relocation assistance not available