Staff Data Scientist, Monetization Products

Key Skills

Apache Hive, Data science techniques, Leadership, Machine learning techniques, Python Programming, R Programming, SQL

Job Description

Our new progressive work model is called PinFlex, a term that’s uniquely Pinterest to describe our flexible approach to living and working. Visit our PinFlex landing page to learn more.

Our mission at Pinterest is to help those people find their inspiration and create a life they love. In the Monetization organization, we take on work that upholds this mission and pushes Pinterest forward. As we innovate on new ads offering, we are looking for an experienced staff data scientist to help influence strategy, solve challenging business and technical problems, and provide guidance and mentorship to talented data scientists and analysts who share this objective. You will be a key voice to co-create and co-pilot new initiatives, seeing them from inception through to technical design, implementation, and release. These initiatives include new ads formats, leveraging generative AI for creative optimization, and shopping products to unblock revenue growth, all the while helping Pinners make their lives better in the positive corner of the internet.

What you’ll do:

• Deep strategic analysis to answer core questions such as: What new ads products should we prioritize to accelerate revenue growth? How to achieve the product market fit for these new ads products?

• Product recommendations. Clearly communicate recommendations to product and engineering teams on how we can evolve our internal strategy and address shortcomings observed through deep analysis. Partner closely with Product to develop and evolve our long-term advertiser growth strategy.

• Opportunity sizing and analysis. Should Pinterest build an ads-only module like competitors? How do we leverage generative AI to optimize creatives? Write clear, actionable analyses that help teams identify areas of improvement and investment.

• Modeling: Build ML models, including design of success metrics and key features and evaluation strategy.

• Experimentation: Improve decision velocity and quality using data scientist tool kit: experimentation, causal inference techniques, etc. Design measurement plans, advise on experimentation best practices, identifying flaws in experiment practices and results; building tools for experiment analysis; collaborative design of new multicell experiment frameworks, counterfactual logging, etc.

• Creating and tracking success metrics. Identify the right measures of success for engineering teams and help them track those metrics. Break down high-level metrics into actionable segments. This work may span from collecting entirely new datasets to building dashboards to track components of a metric (e.g., monitoring conversion data for missing values, implausible values, duplicated data, etc. by advertiser over time).

• Leadership: Lead and mentor the scope of work for data scientists in the same area, demonstrating high-quality output of both yourself and others for whom you are responsible. Provide continuous and candid feedback, recognizing individual strengths and contributions and flagging opportunities to improve performance.

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.

• Proven ability to apply scientific methods to solve real-world problems on web-scale data.

• Expertise in at least one scripting language (ideally Python/R).

• Proficiency in SQL/Hive.

• Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.

• Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams.

• Experience leading key technical projects and substantially influencing the scope and output of others.

• Experience leading key technical projects and substantially influencing the scope and output of others.

• Strong focus on understanding ads domain and advertiser-focused objectives, either through past experience in AdTech or Marketing.

What skills are ideal but not required:

• Exposure to one or more of the following areas is beneficial. Ideal candidates would have exposure to 2+ of these areas and deep familiarity in 1 or more areas.

• Experimentation at web scale or with limited data size. Familiarity with online experimentation and its pitfalls.

• Statistical rigor. Can consult with the team and others on statistically valid approaches to problems.

• Experience in the strategic analytics side of data science: shaping decisions rather than just building models.

This position is not eligible for relocation assistance.

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only

$159,000—$278,000 USD

Our Commitment to Diversity:

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic under federal, state, or local law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require an accommodation during the job application process, please notify accessibility@pinterest.com for support.