Staff Data Scientist

We’re looking for a Staff Data Scientist to lead the science behind how advertisers understand the impact of their investment on Pinterest through first and third party measurement products. You’ll push the boundaries of ads measurement, advancing our approaches to causal inference and incrementality and partner closely with Product and Engineering, as well as represent Pinterest science externally with customers and partners. What you’ll do: 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. What we’re looking for: 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. 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 times per week and therefore needs to be in a commutable distance from one of the following offices San Francisco, Palo Alto, or Seattle. Relocation Statement: This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. #LI-NM4 #LI-REMOTE