Sr. Staff Quantitative Product Researcher, Monetization
PinterestSan Francisco, CA, US; Remote, USPosted 4 March 2026
Job Description
<div class="content-intro"><p><strong>About Pinterest:</strong></p>
<p>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.</p>
<p>Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the <a href="https://www.pinterestcareers.com/our-life/pinflex/">flexibility</a> to do your best work. Creating a career you love? It’s Possible.</p></div><p>Pinterest is looking for a Sr. Staff Quantitative Researcher (Quant UXR) to lead quantitative research at the intersection of our consumer- and advertiser-facing orgs. We’re looking for a seasoned quantitative researcher ready to identify the most important ecosystem-level questions and to create and execute a learning agenda to address them. In this role, you’ll bring expertise in behavioral analysis, statistical modeling, and survey methods to design, execute, and communicate strategic research on a deadline in a fast-paced environment. You’ll uncover opportunities and solutions that balance engagement and revenue goals, present your results to senior audiences, and partner with other leaders to develop strategy that executes on our learnings. With this role, you’ll have ownership of a broad problem space, autonomy to set and execute the learning agenda, and impact over the holistic Pinner experience. <br><br></p>
<p><strong>What you’ll do:</strong></p>
<ul>
<li>Work across monetization teams and as needed collaborate with consumer facing orgs to define and address complex, monetization impacting ecosystem - questions with implications for the business and overall user experience</li>
<li>Proactively guide teams to the most important questions and problems to address for users and/or the business; set the quantitative learning agenda for Monetization and decide on the best approaches to address it</li>
<li>Prioritize and conduct quantitative research that varies in approach, scale, scope, timeframe and methodology, while balancing effort against priority and impact</li>
<li>Explore the intersection of perceptions/attitudes and behaviors through surveys and deep behavioral analysis</li>
<li>Participate in the development of user-centric metrics for Monetization teams while aiding in the development of core centric user metrics</li>
<li>Elevate topics from the learning agenda that would be best to present to senior leadership and tailor deliverables and socialization efforts for these audiences.</li>
<li>Bring together a holistic understanding of the problem space from behavioral analyses, experiment learnings, qualitative insights, and own work to inform product and business decisions </li>
<li>Lead strategic initiatives and actively engage in the development of strategy with Product, Design, Engineering, and Data Science partners</li>
<li>Partner with research managers to set the quantitative research direction and provide guidance to more junior quantitative researchers<br><br></li>
</ul>
<p><strong>What we’re looking for:</strong></p>
<ul>
<li>Bachelor's/Master's degree in a relevant field such as human computer interaction or psychology or equivalent experience</li>
<li>7+ years of experience in quantitative product/user experience research with experience leading end-to-end quantitative research studies; an advanced degree in Statistics, Mathematics, or Economics is a plus but not required</li>
<li>Experience with Ad product development/UX research preferred</li>
<li>Knowledgeable of relevant statistical concepts (significance testing, regression/linear models). </li>
<li>Experience with a wide range of quantitative research approaches and methods, experimentation at scale, various survey methodologies and advanced data techniques ( ... (truncated, view full listing at source)
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