Product Data Scientist, Harvey

• You should be comfortable operating where the data is imperfect, the product is evolving quickly, and the right answer requires both analytical rigor and strong product judgment
• 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 the teams

Desirable

• As a Product Data Scientist, you will be a core member of Harvey's product development organization and one of the foundational members of the Data Science function
• You will partner with Product, Engineering, Design, Go-to-Market, and company leadership to define how we measure product success, understand user behavior, and make high-quality decisions in a fast-moving environment
• This role is both strategic and hands-on
• You will define north-star and product-level metrics, design experiments and causal analyses, build source-of-truth reporting, and turn ambiguous product questions into clear recommendations
• 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