Own the development of measurement methodologies that help advertisers understand and optimize the value of their Pinterest campaigns across the full ads delivery funnel.
Design, implement, and validate advanced causal inference methods for incrementality and lift measurement.
Ensure scientific rigor in our measurement products by anticipating and mitigating risks such as bias, imbalance, and under-power.
Influence Ads Product & Engineering to define the measurement roadmap and integrate science solutions into products and platforms.
Collaborate with internal and external measurement partners (e.g., clean rooms, conversion APIs, MMM partners, MTA vendors) to design and evaluate joint solutions.
Define and own key success metrics for 1P measurement products; build tools and frameworks that enable teams and advertisers to make better decisions.
Provide technical leadership and mentorship to other data scientists and analysts, elevating measurement rigor and impact across the org.
Clearly communicate complex concepts and tradeoffs to executives, cross-functional stakeholders, and external customers.
Requirements
8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data.
5+ years in ads measurement with a strong focus on ad effectiveness and incrementality (e.g., conversion lift, brand lift, budget-split testing, matched-market tests, MMM, MTA).
Proficiency in SQL and expertise in at least one scripting language (ideally Python or R).
Strong business and product sense, with a track record of turning ambiguous questions into well-defined analyses or success metrics and driving decisions that balance scientific rigor and business value.
Demonstrated leadership of key technical projects and meaningful influence on the work of other data scientists, particularly junior and senior peers.
Excellent communication skills and experience leading initiatives across multiple product areas and partnering with leadership and cross-functional teams.
Bachelor’s/Master’s degree in a relevant field such as Computer Science, or equivalent experience.