Staff Data Scientist - Data Platforms

Pinterest brings millions of people the inspiration to create a life they love. To evolve this mission our product and engineering teams need to innovate - much of this innovation is driven through machine learning, and critical to understanding how innovation on the product will change our business is through measurement. Data labels play a key role in unlocking both of these, and the rate and scale at which we can obtain reliable labels limits our speed of innovation.

This role brings together 3 critical science efforts. The notion of asking qualified raters to answer questions about content, whether it’s scoring its relevance to a particular context, review captions for pins, or determining whether or where certain attributes are present in an image, has played a critical role in our evaluation and machine learning efforts across Pinterest. However, utilizing human evaluators to complete these tasks at scale have limitations - it can be time-intensive to accurately define the tasks, costly to get large volumes of labels, and slow to collect the data. Surveys of our Pinners offer a unique mechanism to gather the perspective of our Pinners on questions we have about the platform and content; a Pinner’s perspective can be different to that of a human rater observing the same content because of the unique context they possess. Advancements in Generative AI have opened up a wealth of opportunities for improvements in productivity, and we’ve only scratched the surface of its capabilities in the labeling space. Early results show strong promise for the role it can play in these tasks, reducing the time and cost of our labeling efforts, focusing our surveys and human rater efforts on higher value problems, and improving the accuracy of our learnings.

We’re looking for an accomplished Data Scientist to unlock a new level of capabilities in our efforts across labeling, surveys, and iterative GenAI tasks. From statistical approaches that can better inform the labels we collect to prototypes to automatically craft prompts for LLMs to address the needed tasks, you will be improving the quality of our decisions and the velocity with which we can obtain reliable insights.

What you’ll do:

• Build a roster of high-impact analytical opportunities that improve velocity, clarity and trust in our labeled data collection solutions.

• Collaborate with customers of the platforms to understand whether data observations reflect their problems and pain-points, and with engineers to scale your successful prototypes to become integral components of the platform.

• Up-level data scientists across the organization through mentorship, partnership and constructive feedback.

• Contribute to a strategic vision for the science investments across the labeling, survey and GenAI tooling space, emphasizing rigor alongside value-creation, and partner with product and engineering leaders to build a unified vision for these platforms.

• Communicate complex analytical findings and insights to both technical and non-technical audiences in a clear and concise manner.

• Collaborate cross-functionally with customers to understand their problems and pain-points, and with engineers to scale successful prototypes to become integral components of the platform.

What we’re looking for:

• 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on large-scale data 

• 5+ years of hands-on experience as an individual contributor using a deep understanding of scientific methods applied to data to drive business decisions

• Proven track record of crafting high quality algorithmic code and identifying opportunities for efficiency and performance improvements through statistical methods

• Domain expertise in at least one area across: data labeling, surveys, LLM development

• Demonstrated execution and impact on cross-functional initiatives, strong communication skills, and a track record of influencing leaders and peers using data

• Self-propelled continuous learner who keeps up with new tools and methodologies and builds prototypes with concepts learned

• Strong business and product sense who can shape vague questions into well-defined analyses and success metrics that drive business decisions

• Bachelor’s/Master’s degree in a relevant field such as Computer Science, or equivalent experience

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/quarter and therefore can be situated anywhere in the country.

Relocation Statement

• This position is not eligible for relocation assistance.

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