Data Scientist

We're doing an AI-first engineering rebuild for a company that already has an audience of 100M+ people. This is a zero-to-one build with no legacy constraints. You're not here to run reports or maintain someone else's dashboards. You're here to turn ambiguous product questions into clear, data-backed answers that directly shape what we build and how we grow. You'll work alongside engineers and product teams, using AI to move faster than a traditional data science workflow ever allowed.

The Product You'll work as part of a small, fast-moving team on the data foundation that powers product decisions across consumer products, media, gaming, and e-commerce. The work spans the full journey from raw user behavior to actionable insight. That means:

• Product questions that are ambiguous, high-stakes, and time-sensitive. You need to frame them correctly before you can answer them.
• A/B experiments where the design, statistical rigor, and interpretation directly determine what ships next.
• A fast-moving team that moves at a pace where every analysis needs to count, and AI tools are a core part of how we get there.

What You'll Do

• Design and execute analyses that turn raw user behavior into actionable product insights, working closely with engineers and product teams to frame the right questions.
• Own A/B experiments end to end, from experiment design and statistical analysis through to result interpretation and recommendation.
• Communicate findings clearly to product and engineering stakeholders, translating complex analysis into actionable recommendations that drive product decisions.
• Leverage AI tools to accelerate your workflow, from data exploration and analysis to insight delivery and iteration.

Who You Are

• AI-Native: You're already using AI tools daily to move faster, from writing queries and building models to exploring data and communicating findings.
• Analytical Builder: +3 years of hands-on experience in data science or analytics, with strong SQL, Python, and statistical modeling skills. You don't just analyze. You build the tooling and frameworks that make analysis repeatable and reliable.
• Product Connected: You care about why you're analyzing something, not just how. You can translate vague product questions into tractable data problems and communicate findings clearly to non-technical stakeholders.
• Experimentally Rigorous: You understand the principles of A/B testing, know where experiments go wrong, and hold the line on statistical rigor even under deadline pressure.
• Strong SQL and Python skills, experience with A/B experimentation frameworks, and familiarity with at least one major cloud data stack (AWS, GCP, Databricks, Snowflake, or equivalent). Bonus points for experience in consumer products, media, gaming, or e-commerce, and prior work alongside product or engineering teams in a fast-moving environment.

Compensation: $178,000 –$223,000 base + equity + benefits Hybrid Model: Expected ~3 days per week in-office (San Mateo, CA)