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# Lead Data Scientist, Product

- **Company:** Descript
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $200,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Database Queries, Python (Programming Language)
- **Published:** July 17, 2026
- **Apply:** https://www.dice.com/job-detail/273212d5-2ef2-412b-a267-d944e9c8cea8

## About the Role

* 5-8 years of experience in a Data Scientist or similar role.
 * 3+ years working in a growth function.
 * Strong business and product intuition to identify opportunities in the growth ecosystem.
 * Strong knowledge of statistical analysis and A/B tests.
 * Strong SQL skills and proficient in at least one programming language such as Python or R.
 * Excellent communication and collaboration skills.
 * Curiosity, savviness to navigate in a dynamic environment, and a growth mindset.
 * Having worked at a fast-growing start-up is a plus.

The base salary range for this role is $200,000 - $250,000/year. Final offer amounts will carefully consider multiple factors, including prior experience, expertise, location, level, and may vary from the amount above.

## Description

As a founding product data scientist on the team, you will play a critical role in shaping our growth strategy, up-leveling our experimentation culture, and scaling our business.
What You'll Do

 * Conduct in-depth analysis to shape product PLG motion and B2B strategy.
 * Develop deep understanding of the product ecosystem and identify opportunities to drive activation, engagement, and monetization through actionable insights.
 * Leveraging AI tools to build and maintain self-service analytics enabling stakeholders to access reliable metrics, size opportunities, design experiments, and interpret results independently.
 * Improve execution rigor of product teams by owning success metrics and opportunity sizing.
 * Brain buddy with product and engineering teams for day-to-day experiment design, deployment, and analysis. Provide creative solutions for tricky experimentation scenarios.
 * Evolve experimentation culture and practices within the company.


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