Clay Labs

Data Scientist at Clay Labs (San Francisco, CA)

Clay Labs· San Francisco, CA· $170k–$300k·

Role details

Salary
$170k–$300k
Work type
Hybrid
Employment
Full-Time
Equity
Yes

Clay Labs at a glance

A go-to-market platform that pairs a 150+ provider data marketplace with AI agents and workflow automation so revenue teams can build, not just buy, their growth systems.

Clay is a go-to-market platform that combines a 150-plus-provider data marketplace, AI research agents (Claygent), and workflow automation so revenue teams can enrich data, research prospects, and run automated outbound from one canvas.

$204M raised · latest: Employee tender offer at $5B valuation · Jan 2026 (last priced round: Series C · $100M · Aug 2025 · $3.1B) · backed by CapitalG, Sequoia Capital, First Round Capital, Meritech Capital Partners

Job description

About Clay

AI is unleashing the biggest wave of company creation in history. Clay's mission is to be the engine those companies use to grow to their full potential. Clay predicts the next best action for your business and then helps you take it. We started by aggregating the best data for B2B companies. Then, we built the infrastructure to run any personalized campaign on top of it, including emails, ads, landing pages, and workflows that make reps more productive. Now, we're building agents that can help grow your company for you. We're already helping thousands of customers — including Anthropic, OpenAI, Google, and Visa — go to market with unique data, signals, and AI research. In 2026, we raised a $115M Series D at $7.1B Valuation led by Wellington — and are on track to cross $200M in revenue this quarter. We also launched a $1M Scholarship fund for GTME Education. Some things to know about us:

  • Our community includes 17,000+ customers, 200+ integration partners, 125+ agencies, 50+ Clay clubs, and 30k members on Slack.
  • Our culture is unique inside and outside of work. Our team members are also DJs, activists, writers, clowns, marathoners, skydivers, psychedelic therapists, social workers, and more.
  • All employees can work with world-class coaches who specialize in creativity, management, and more.
  • Our operating principles — including negative maintenance and non-attached action — guide our work. Read more about them here.
  • Read about us in the NYT, Forbes, First Round Review, and more.

Hear from our employees directly on our Glassdoor page!

Data Scientist @ Clay We're looking for a Data Scientist to join Clay's Data Science and Analytics team. You'll be durably embedded with a partner team—Product, Marketing, Sales, Finance, or Partnerships—as their full data partner, with the deep context to shape what gets built and how the business runs, backed by a central data team that operates as one center of excellence. This role is for someone who wants to own challenging, ambiguous problems end to end: designing experiments, building predictive models, and designing new metrics to guide out business. Data scientists at Clay are strategic leaders and trusted truth-tellers. Plus, we are among the fastest growing AI businesses, and our team is at the bleeding edge of AI-enabled data science.

What You'll Do

Own causal inference and experimentation Design and analyze experiments, and build incrementality measurement where clean A/B tests aren't possible (e.g., propensity-score matching to estimate true lift of features and GTM channels). Define how we measure the business Shape metric trees that connect team-level metrics to company outcomes, establish success criteria for product launches, and build frameworks for sizing and forecasting impact. Build predictive models that lead our team to focus on what matters most. Go deep on the toughest questions Root-cause anomalies, investigate nuanced behavioral questions, and build new analysis frameworks where existing patterns don't fit. Use data to teach all of Clay what we should be focusing on and what we can ignore. Partner as an embedded expert Work as the direct analytical partner to leaders in your area, turning ambiguous strategic questions into rigorous, decision-ready analysis.

What You'll Bring

5+ years in data science, with demonstrated ownership of experimentation, causal inference, or predictive modeling Strong product and business sense: you connect analysis to decisions and revenue and have a demonstrated track record of directly influencing product and business decisions with your work Strong statistical and experimentation foundations: experiment design, effect estimation, a large exploratory analysis toolkit, and knowing when a result shouldn't be trusted Expert SQL and Python Experience using AI tools (Claude Code, Cursor, or similar) to accelerate analytical work: our team is AI-forward, and our workflows heavily utilize these tools Clear communicator who can influence senior stakeholders

Nice To Haves Experience with our stack: Snowflake, Github, dbt, Hex, Sigma, Dagster Experience in product-led growth or B2B SaaS, especially usage-based pricing Experience partnering with ML engineers to productionize models

Why Clay

At Clay, AI handles routine analytical questions, so your time goes to the problems that require your expertise: causal inference, prediction, and the deep dives that change decisions. You'll help shape how a fast-scaling company measures growth and makes decisions. We value ownership, thoughtfulness, creative problem-solving, and a relentless focus on impact.

Why work at Clay Labs

  • Culture: Kindness, creativity, “quiet ego”, and a focus on helping each other grow. Values like “Make it work, then make it great” and “Negative maintenance” (improve a little every day).
  • Work model: Flexible in‑person culture – office in Chelsea, NYC, with daily team lunches and DJ Fridays. Hybrid flexibility offered; remote roles available.
  • Benefits: Competitive salary, fully funded health/dental/vision, 4 months paid parental leave, IVF and egg freezing benefits, flexible PTO, yearly company retreats, visa sponsorship.
  • Engineering: Emphasis on craft, attention to detail, and deep enjoyment of the building process. Engineers work on AI, data infrastructure, and scalable systems.
  • Interview process: Typically 3–5 interviews (behavioral + technical) plus a founders interview; practical exercises and reference checks.

Application questions