H

Harvey

Builds AI software for lawyers

Data Scientist - Product

Data ScienceConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$155k - $260k /yrHybrid

About the Job

Requirements

  • At least 5 years of experience in data science, product analytics, economics, statistics, or another quantitative field, ideally in a high-growth product company, AI company, research organization, or similarly ambiguous environment.
  • A strong track record of using SQL, Python, and statistical methods to answer product questions and turn analysis into product or business impact.
  • Experience defining new metrics and measurement frameworks from scratch, especially for products where usage patterns, customer value, or success criteria are still being discovered.
  • Deep fluency in experimentation, causal inference, A/B testing, and statistical modeling, with good judgment about when precision matters and when directional clarity is enough.
  • Strong product instincts and curiosity about how users adopt, evaluate, and expand their use of AI-enabled workflows.
  • Excellent written and verbal communication skills, including the ability to influence Product, Engineering, Go-to-Market, and executive stakeholders through clear reasoning and compelling data stories.
  • Comfort creating structure in fast-moving, ambiguous environments and raising the quality of decision-making for teams.

Responsibilities

  • Embed with Product and Engineering teams as a trusted analytical partner, identifying opportunities to improve user experience, adoption, retention, and business impact.
  • Define and maintain core metrics that create a shared understanding of product performance and customer value.
  • Design and evaluate experiments, including A/B tests and causal inference methods, to measure the impact of product, model, and workflow changes.
  • Analyze product usage, customer segments, and go-to-market signals to surface insights, size opportunities, and inform roadmap decisions.
  • Build dashboards, reports, and self-serve tools that help teams answer product questions with confidence.
  • Develop models, forecasts, and analytical frameworks to explain user behavior, detect anomalies, and guide prioritization.
  • Translate complex analyses into clear recommendations for technical, business, and executive audiences.
  • Partner with Engineering and Data teams to improve the infrastructure that powers analytics, experimentation, and decision-making.
  • Establish the standards, practices, and culture for Product Data Science at Harvey.

Desired Qualifications

  • Experience with AI/ML products, large language models, developer tools, enterprise software, or products used in complex professional workflows.
  • Experience as an early data science or analytics hire at a hyper-growth startup, including helping define team norms, tooling, and best practices.
  • Experience supporting enterprise or B2B products, including analysis of adoption, engagement, retention, expansion, or go-to-market motion.
  • Familiarity with modern data infrastructure and the practical tradeoffs involved in building reliable analytics in a rapidly evolving product environment.

About the Company

Harvey

Builds AI software for lawyers

Harvey builds AI software made specifically for legal work, used by lawyers at large law firms and corporate legal departments. It became one of the first generative AI tools rolled out across a major law firm when Allen & Overy gave it to its lawyers worldwide in 2023. Lawyers use Harvey to research legal questions, draft and review contracts, and run due diligence across large sets of documents, with answers grounded in their firm's own files and trusted legal sources. Firms pay through enterprise subscriptions, and Harvey can tailor its workflows to practice areas such as litigation and mergers. Harvey was founded in 2022 with early backing from the OpenAI Startup Fund and is based in San Francisco.

Company size
1,001-5,000
Company stage
Late Stage VC
Total funding
$1.8B
Headquarters
San Francisco, CA
Founded
2022

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