Senior Data Scientist, Growth Product
Senior Growth Product Data Scientist partnering with Product and Engineering to drive experimentation, build metrics, and deliver data-driven recommendations that improve acquisition, conversion, and retention.
Responsibilities
- Operate as an independent thought partner to Product, Engineering, and Design — helping shape strategy, not just measure it. Proactively identify opportunities and risks, framing the right questions before they’re even asked.
- Work with the team to develop a rich program of experimentation and A/B testing to improve member product experiences, including metric creation, experiment design, power analysis, and analysis of experiment results.
- 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 metrics to measure user funnels, product engagement, and retention, and use those metrics to help brainstorm potential product experiments to drive improvements in them.
- Help the team establish high-quality eventing to allow the tracking of detailed user behaviors along customer journeys through Chime’s mobile app.
- Develop and evolve team metrics that define what “good” looks like — ensuring that we optimize for long-term member and business value – and build operational dashboards to track business and product health.
- Translate complex analytical findings into compelling, executive-ready narratives that inspire action and alignment across teams.
- Develop robust data pipelines in dbt for your team, and continuously improve the quality and accessibility of customer data.
Requirements
- 5-7 years of relevant hands-on experience in product or business analytics roles (FinTech a plus).
- Expert-level SQL ability and proficiency in Python.
- Broad knowledge of applied statistics, experimental design, and analysis of A/B tests. Demonstrated experience with machine learning techniques for applied business use cases.
- 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).
- Exceptional data storytelling and data visualization ability. Experience with Hex and Looker.
- Familiarity with building data pipelines using tools like dbt or Airflow.
- Familiarity with AI coding tools (such as Claude Code and Cursor).
Compensation & Benefits
- Base salary: $133,000 – $185,000
- Eligible for bonus, competitive equity package, and benefits.
Senior Data Scientist, Causal Inference
Lead causal inference and marketing mix modeling efforts to measure and optimize marketing investments for Lyft's Growth Products team. Requires 4+ years experience, advanced degree, and expertise in Python, SQL, and causal methods.
Senior Data Scientist, Causal Inference
Lead causal inference and marketing mix modeling efforts to measure and optimize marketing investments. Requires 4+ years experience, advanced degree, and expertise in Python, SQL, and production environments.
Senior Data Scientist, Causal Inference
Lead causal inference and marketing mix modeling efforts to measure and optimize marketing investments. Requires 4+ years experience, advanced degree, and expertise in Python, SQL, and statistical pipelines.