Product Data Scientist: Metrics & Experiments

Harvey; California (MO); On-site; USD 155,000 - 260,000; Full time

Job summary

Harvey is seeking a Product Data Scientist to join our core product development team. You will partner with Product, Engineering, Design, and Go-to-Market to define how we measure product success, understand user behavior, and drive data-informed decisions in a fast-moving environment.

This role blends strategic thinking with hands-on analysis, including defining north-star metrics, designing experiments, building reporting, and turning ambiguous questions into actionable recommendations.

Qualifications

• 5+ years of experience in data science, product analytics, economics, statistics, or another quantitative field.
• Strong track record of using SQL, Python, and statistical methods to answer product questions and drive impact.
• Experience defining new metrics and measurement frameworks from scratch for evolving products.

Responsibilities

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

Skills

SQL

Python

Statistical methods

Job description

Harvey is seeking a Product Data Scientist to join our core product development team. You will partner with Product, Engineering, Design, and Go-to-Market to define how we measure product success, understand user behavior, and drive data-informed decisions in a fast-moving environment.

This role blends strategic thinking with hands-on analysis, including defining north-star metrics, designing experiments, building reporting, and turning ambiguous questions into actionable recommendations.