Pinterest’s ad business is critical to its success. Our ads measurement strategy is fundamental to understanding how Pinterest adds value to advertisers, how we convey this value and how we differentiate the efficacy of different ad products. We’re hiring a data scientist to help influence this strategy, solve crucial measurement challenges and collaborate with a team of talented data scientists and analysts who share this objective.

What you’ll do

• Deep strategic analysis to improve our understanding of our advertising platform and its ability to enable us to meet advertiser objectives. Answer core ads measurement questions such as: How can we prove the effectiveness of ads to advertisers? Can we quantify how new ad features will impact key business metrics? How accurate is our offsite conversion data, and how well can we match incoming conversions to Pinterest users? What features of a conversion can help us inform decisions on ad distribution?
• Product recommendations. Clearly communicate recommendations to Product and Engineering teams on how we can evolve our internal strategy to address shortcomings observed through deep analysis. Partner closely with Product to develop and evolve our long-term advertiser measurement strategy.
• Opportunity sizing and analysis. Where is attribution breaking down? Are our brand lift studies biased? What do people do on Pinterest before purchasing? How closely related are the products that a user viewed and purchased? Write clear, actionable analyses that help teams identify areas of improvement and investment.
• Experimentation: Evolve our experimentation capabilities and tools to evaluate the efficacy of our ad products on advertiser goals and KPIs. Advise on experimentation best practices; identify flaws in experiment practices and results; build tools and frameworks for experiment analysis.

What we’re looking for:

• 4+ 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)
• 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 communicate findings with leadership and product teams 

The best candidates will also have:

• Strong focus on understanding ads domain and advertiser-focused objectives, measuring ad effectiveness, or similar.
• Experience with experimentation at web scale. Familiarity with online experimentation and its pitfalls.
• Experience in the strategic analytics side of data science: shaping decisions rather than just building models
• Proficiency in SQL/Hive

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