Data Scientist, Marketing Science

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.

Millions of people across the world come to Pinterest to find new ideas every day. It’s where they get inspiration, dream about new possibilities and plan for what matters most. Brands and products are a critical piece of this journey, enabling Pinners to move easily from inspiration to action and advertisers to realize value in connecting with users with high commercial intent.

As Pinterest continues to scale, we need insightful analyses and actionable recommendations to help maximize value to both Pinners and advertisers. Tasked with such vision, we are looking for data scientists to jump start Pinterest’s Marketing Science team. You will take end-to-end ownership of designing, researching, building, and delivering data products as well as collaborate with XFNs to formulate, experiment, and evolve Pinterest’s best practice guides to advertiser performance.

You will support strategic planning, marketing events, earnings releases, and other efforts with powerful data narratives.

• Research and analyze what drives performance on our platform for advertisers.
• Monitor key trends in ads performance to identify and scale platform-level improvement opportunities and/or flag and mitigate risks of reduction.
• Equip the business with data-backed recommendations that deliver the strongest performance outcomes, tailored to key advertiser segments, defined by dimensions including marketing objective, campaign type or measurement source of truth, etc.
• Creating and tracking metrics around advertiser value.
• Identify the right framework to quantify the value Pinterest provides to advertisers, and drive XFN alignment on implement and monitor those metrics as north stars of success.
• Improve decision velocity and quality using data scientist toolkit: experimentation, causal inference techniques, etc. Design measurement strategy, advise on experimentation best practices, identifying flaws in experiment practices and results; building tools for experiment analysis etc.
• 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.

• MS or PhD in a quantitative field or equivalent experience
• 8+ years of experience applying data science to solve real-world problems on web-scale data
• Domain expertise about ads platforms and products, particularly around measurement and performance
• Strong fundamentals in statistics, particularly experimentation and causal inference
• Proficiency in common data science coding languages such as SQL and Python.
• Proven track record of driving data science projects and/or initiatives in a cross-functional team including both technical and non-technical stakeholders.
• Strong communication skills. Explains work and thought processes clearly, concisely and convincingly.

• 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 1x week and therefore needs to be in a commutable distance from one of the following offices:
  Seattle, San Francisco and Palo Alto.

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

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