Data Scientist, Handshake AI

Handshake AI is the fastest-growing, most critical, and most revenue-generating part of Handshake's business. We power expert-labeled data collection at scale, matching domain experts with leading AI companies to train frontier models—and we're already a top-three player in one of the fastest-growing sectors in AI: human data. We have the opportunity to do for the AI data economy what LinkedIn did for professional networking: become the default platform where the work happens.

Why join Handshake now:

• Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel

• Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world's top educational institutions

• Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others

• Build a massive, fast-growing business with billions in revenue

We’re looking for a highly motivated Data Scientist with strong SQL expertise to support analytics, measurement, and operational insights across our human data training workflows. You’ll work with messy, fast-moving data related to expert performance, task quality, throughput, and overall operational efficiency.

This is a hands-on role with real ownership, close partnership with product and operations, and a steep growth curve for someone who executes well.

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  Write advanced SQL to analyze large, complex datasets related to expert performance, task quality, and operational workflows.

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  Define, build, and maintain core metrics that measure data quality, throughput, productivity, and operational efficiency.

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  Partner with Product, Operations, and cross-functional stakeholders to answer high-impact business and product questions.

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  Conduct analyses that inform workflow design, task improvements, and operational decision-making.

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  Build dashboards, reporting, and self-serve analytics that enable fast, informed decisions.

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  Identify data gaps, inconsistencies, and quality issues, then partner with relevant teams to resolve them.

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  Translate ambiguous business questions into clear analyses and actionable recommendations.

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  Communicate findings and recommendations clearly to both technical and non-technical stakeholders.

• 3–5 years of experience in Data Science, Product Analytics, Business Intelligence, or a related analytical role.

• Expert-level SQL skills and experience working with large, complex datasets.

• Strong analytical judgment and comfort working with imperfect, real-world data.

• Experience defining metrics and using data to influence product or business decisions.

• High ownership mindset and ability to independently drive complex work forward.

• Strong communication skills and comfort partnering cross-functionally in a fast-paced environment.

• Python experience for data analysis, such as pandas and notebooks.

• Experience supporting operational, marketplace, quality, or workforce-related analytics.

• Experience with experimentation, A/B testing, or metrics-driven product development.

• Exposure to AI data workflows, data labeling, or evaluation processes.

• Experience with analytics engineering, including building and maintaining DBT models.