Staff Data Scientist, Ad Measurement Products

Confirmed live in the last 24 hours

San Francisco, CA, US; Remote, US

Remote

Posted March 27, 2026

Job Description

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.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

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

Design, implement, and validate advanced causal inference methods for incrementality and lift measurement.
Apply AI/ML techniques and AI-assisted workflows to improve the scale, speed, and quality of ads measurement, experimentation, and insight generation across first- and third-party measurement products.
Ensure scientific rigor in our measurement products by anticipating and mitigating risks such as bias, imbalance, under-power, and data quality issues, including those that may arise from AI-enabled systems.
Influence Ads Product and Engineering to define the measurement roadmap and integrate science and AI-powered solutions into products and platforms including model-driven diagnostics, anomaly detection, automated insight generation, and decision-support for advertisers.
Collaborate with internal and external measurement partners, such as clean rooms, conversion APIs, MMM partners, and MTA vendors, to design and evaluate joint solutions.
Define and own key success metrics for first-party 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, external customers, and partners, including the opportunities and limitations of AI-based approaches.

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.
Experience applying AI/ML methods or AI-assisted workflows to analytics, experimentation, measurement, or product problems.
Strong judgment in evaluating AI-generated outputs and translating them into reliable, explainable, and scientifically sound solutions.
Demonstrated leadership of key technical projects and meaningful influence on the work of