Lead Data Scientist

Snorkel AI
San Francisco, CA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
0 years minimum
Compensation
$130,000.0 - $200,000.0
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Artificial Intelligence Data Analysis ARM Architecture Data as a Services Data Architecture Data Infrastructure Data Warehousing Fraud Prevention and Detection Python (Programming Language) SQL Databases Large Language Models
+6 more
Snowflake Generative AI Data Layers Data Analytics Streamlit Framework Marketplace

Job description

This role is hybrid (3 days/week in office) in San Francisco, CA. Our Data & Analytics Platform team recently migrated from Redshift to Snowflake, enabled 100+ users, and centralized all business data in under three months. We are a lean team with a clear remit: ensure a single source of truth for all business data. With company-wide Snowflake adoption complete, we are hiring a Lead Data Scientist to expand our mandate to Generative AI Analytics and Snorkel’s highest-leverage data science problems.

This is a senior individual contributor role with no direct reports; just ownership, autonomy, and impact from pioneering new insights and models and building our semantic layer, supply/demand matching algorithms, forecasting models, and other data science foundations that compound.

How you’ll allocate your time (estimates subject to change):

  • 40%: Building and maintaining Generative AI Analytics
  • 40%: Critical-path data science projects
  • 20%: Partnering with Engineers, PMs, DaaS operational leads, and Finance, * Own Generative AI Analytics: Build and maintain end-to-end infra (semantic layer, LLM tooling, evals, and agents) to analytically empower every team at Snorkel.
  • Protect Quality: Work with Engineering and the Fraud Operations Lead to build, unify inputs for, and deploy fraud detection and contributor quality models.
  • Optimize Marketplace: Architect search, ranking, and recommendation models to match project needs for Expert Contributors across domains and geographies.
  • Improve Forecasting: Build predictive models to help Strategy & Operations and Finance elevate forecast accuracy with signals from across the business.
  • Identify Leverage: Surface the next high-value data science opportunities at Snorkel and build the case for their prioritization with the Head of Data.
  • Advise Leadership: Be a trusted thought partner to the Head of Data and leaders of other teams on data architecture, applied data science, and AI.

Requirements

  • 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.
  • Modern AI Tools: Experience deploying modern AI tools (semantic layers, LLMs, evaluation frameworks) reliably into production.
  • Engineering Collaboration: Proven ability to partner with Engineering teams to bridge the gap from prototype to production system.
  • 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.
  • Partnership: Genuinely values engaging technical and operational stakeholders to fully understand a problem and build data-driven solutions.

Bonus Points: Experience with Streamlit, Snowflake Cortex, AI/data labeling, A/B testing, and two-sided marketplace or data product business models.

Pay Transparency Notice: Depending on your work location, the target annual salary for this position can range as detailed below. Snorkel also includes benefits (including medical, dental, vision and 401(k)). All offers include equity compensation in the form of employee stock options. This role is hybrid (3 days/week in office) in San Francisco, CA.

About the company

About Snorkel

At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.

We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

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