Lead Data Scientist, Product

Location: San Francisco, CA or Remote, US

Department: Product & Design

Our vision is to build the next generation platform to enable easy and fast creation of audio and video content powered by cutting-edge AI. Building a revolutionary way to record, transcribe, edit, and mix spoken audio and video comes with a series of unique challenges and requires solving hard and complex problems.

As a lead 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.

What You Bring

• 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.