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Lead Data Scientist

Snorkel AI · San Francisco, United States

External listingfull-time20 days ago

About The Role

Join Snorkel, a leading company in the field of data and analytics. As a Lead Data Scientist, you will have the opportunity to make a significant impact by pioneering new insights and models, building our semantic layer, and optimizing our marketplace. You will work closely with engineers, product managers, and operational leads, and have the autonomy to drive critical data science projects. Enjoy a comprehensive benefits package, unlimited personal time off, and the chance to be part of a global team.

  • Lead the development and maintenance of Generative AI Analytics, including the end-to-end infrastructure for semantic layers, LLM tooling, evaluations, and agents.
  • Architect and implement critical-path data science projects, including fraud detection, contributor quality models, search, ranking, and recommendation models.
  • Collaborate with cross-functional teams, including Engineers, PMs, and operational leads, to ensure the successful deployment of data science solutions and to identify high-value opportunities.
  • Bonus Points: Experience with Streamlit, Snowflake Cortex, AI/data labeling, A/B testing, and two-sided marketplace or data product business models
  • Agency: Strong track record of impact without a large team or detailed roadmap
  • 0-to-1 Mindset: Comfortable building foundational systems from scratch in environments where data infrastructure is still maturing
  • Engineering Collaboration: Proven ability to partner with Engineering teams to bridge the gap from prototype to production system
  • Modern AI Tools: Experience deploying modern AI tools (semantic layers, LLMs, evaluation frameworks) reliably into production
  • Partnership: Genuinely values engaging technical and operational stakeholders to fully understand a problem and build data-driven solutions
  • 5+ years: data science or related experience, with a track record of shipping forecasting, ranking, recommendation, or similar models into production
  • Tech Stack: SQL, Snowflake or a similar data warehouse, and Python experience

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