Data Scientist, Growth Product

Requirements

• 3-5 years of relevant hands‑on experience in product or business analytics roles (FinTech a plus)
• Expert‑level SQL ability and proficiency in Python
• Hands‑on experience designing and analyzing A/B tests; solid grasp of statistical concepts (significance, power, sample size, common pitfalls)
• Demonstrated experience acting as a trusted advisor to senior cross‑functional partners — influencing decisions through both data and judgment
• A strong bias toward proactive problem discovery. You don’t wait for tickets — you explore data, spot patterns, and bring forward opportunities that meaningfully change product direction
• Strong business intuition and judgment, and experience applying prioritization frameworks to your work (e.g., RICE, Eisenhower matrix)
• Strong written and verbal communication; able to translate technical concepts to non‑technical stakeholders
• Familiarity with building data pipelines using tools like dbt or Airflow
• Familiarity with AI coding tools (such as Claude Code and Cursor)
• Located within commuting distance from our downtown San Francisco headquarters, and able to work in‑office with our team 4 days per week

What the job involves

• Partner with Product Managers, Engineers, Designers, and Marketers on growth initiatives spanning acquisition, onboarding, activation, and retention
• Design, run, and analyze A/B tests to improve member product experiences, including metric creation, experiment design, power analysis, and analysis of experiment results; develop frameworks to prioritize the highest‑leverage experiments
• Drive data‑informed decision making within Growth org by equipping PMs and engineers with self‑service analytics tools, and conducting ad‑hoc analyses and causal studies for the team
• Use advanced statistical methods for causal inference, as well as time‑series and other forecasting techniques, to solve product questions for the team. Occasionally apply machine learning methods for problems such as customer segmentation
• Build and maintain dashboards, KPIs, and self‑serve tooling that give the team a clear view of funnel health
• Help the team establish high‑quality eventing to allow the tracking of detailed user behaviors along customer journeys through Chime’s mobile app
• Translate complex analyses into clear narratives and recommendations for product and executive audiences
• Collaborate with Data Engineering to improve the quality, accessibility, and trustworthiness of growth datasets