Senior Data Scientist

Primary: Bay Area (San Francisco / Peninsula)   |   Secondary: NYC

The Opportunity

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, so your analysis and models shape the foundation instead of explaining an old one. You're here to turn data into decisions that move the business for one of the largest audiences on the planet.

The Work

You'll apply advanced statistics, experimentation, and machine learning to hard business problems, partnering with product, engineering, operations, and business leaders to find opportunities and prove impact. That means:

• Ship predictive models, experiments, and decision-support analytics that move key business KPIs.
• Build a privacy-safe understanding of a 100M+ audience that powers product and partner decisions.
• Raise the bar on experimentation and causal analysis, and bring AI tooling into the workflow where it helps.

What You'll Do

• Lead end-to-end data science projects from problem definition through deployment and measurement.
• Design, build, validate, and maintain statistical and machine learning models.
• Partner with stakeholders to turn business objectives into analytical approaches and success metrics.
• Run experimentation, causal analysis, and hypothesis testing to guide real decisions.
• Communicate complex findings to technical and non-technical audiences through clear storytelling.
• Build scalable analytical frameworks and reusable assets, and set data-quality standards.
• Mentor junior data scientists and analysts, and partner with engineering to productionize models.

Who You Are

• AI-Native: You're already using AI in your daily workflow to move faster from question to insight to shipped model.
• Rigorous Analyst: Typically 6+ years in data science or advanced analytics, with deep expertise in statistical modeling, experimentation, and machine learning, plus strong SQL and Python or R.
• Business-Impact Driven: You've influenced real business decisions with data, and you measure success by adoption and outcomes, not just model metrics.
• Clear Communicator: You use evidence to challenge assumptions, explain complex ideas to anyone, and hold a high bar for rigor and reproducibility.

Bonus points for a Master's or PhD in a quantitative field, deploying ML models to production, cloud-based analytics and ML platforms, and mentoring data scientists or leading cross-functional initiatives.

Benefits

• Equity: Highly competitive equity package designed for a foundational hire.
• Hybrid Model: Expected ~2 days per week in-office (Bay Area or NYC).