We are looking for a Senior Data Scientist. You will shape the future of people-facing and business-facing products we build at Pinterest. Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Design, Research, Product Analytics, Data Engineering and others. The results of your work will influence and uplevel our product development teams while introducing greater scientific rigor into the real world products serving hundreds of millions of pinners, creators, advertisers and merchants around the world.

What you’ll do:

• Develop best practices for instrumentation and experimentation and communicate those to product engineering teams to help us fulfill our mission - to bring everyone the inspiration to create a life they love.
• Bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of our Pinners.
• Build and prototype analysis pipelines iteratively to provide insights at scale while developing comprehensive knowledge of data structures and metrics, advocating for changes where needed for product development.
• Work cross-functionally to build and communicate key insights, and collaborate closely with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest.
• Leverage AI to seek faster execution (i.e. draft, prototype, outline) and explore alternative options (i.e. iterate, compare approaches).
• Leverage AI to synthesize information (summarize, distill themes) and automate repeatable tasks (documentation, reporting, QA checks).
  
  

What we’re looking for:

• 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data.
• Extensive experience solving analytical problems using quantitative approaches including in the fields of Statistics, Machine Learning, Forecasting, Econometrics or other related fields.
• Experience solving problems within digital advertising is preferred.
• Familiarity with online experimentation and its pitfalls.
• A scientifically and statistically rigorous approach to analysis and data.  You rely on statistically valid approaches to problems and have a well-tuned sense of skepticism, attention to detail and commitment to high-quality, results-oriented output.
• Ability to manipulate large data sets with high dimensionality and complexity; fluency in SQL (or other database languages) and a scripting language (Python or R).
• Excellent communication skills and ability to explain learnings to both technical and non-technical partners, including Product and Machine Learning teams.
• A team player who’s able to partner with cross-functional leadership to quickly turn insights into actions.
• Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
• Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review).
• High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
• Bachelor’s or Master’s degree in a relevant field such as Data Science, or equivalent experience.

This job posting is for an open vacancy. Please note that the company utilizes artificial intelligence to screen applicants for the positions.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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 1-2 times per half and therefore can be situated anywhere in Ontario. 

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