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Salary: USD 155,000 - 187,000 / annual
Flex is a growth-stage fintech company headquartered in NYC that is transforming rent payment by enabling users to pay throughout the month on flexible schedules. The company is expanding into a broader consumer bill management platform (Control Center) and seeking a Staff Data Scientist to lead the data foundation and analytics strategy for this new vertical.
In this role, you will operate as both the builder of the data infrastructure and the analyst driving business decisions. You'll work closely with business leadership, product, engineering, and risk teams to establish data standards and insights that power the platform's growth from pilot to scale.
Key responsibilities include:
- Building and maintaining core data models using dbt and Snowflake that support reporting, experimentation, and ML/credit risk use cases
- Analyzing consumer bill payment behavior, including timing, splitting, delinquency patterns, and credit-building outcomes to identify what's working in the pilot
- Partnering with Product and Engineering to instrument new features (bill splitting, smart scheduling, credit-building) and measure adoption and impact from launch
- Designing and analyzing experiments (A/B tests, quasi-experimental methods) to test pricing, credit terms, and product flows, establishing causal links between changes and outcomes
- Creating dashboards and self-serve analytics tools that enable Product, Risk, and GTM teams to track key metrics independently
- Championing data quality, consistent terminology, and documentation as the data footprint scales
- Setting technical direction for how data models and pipelines scale as new billers, partners, and product surfaces launch; mentoring other analysts and engineers
You'll need 5+ years of experience spanning analytics engineering and data science/analyst work, with strong SQL, hands-on dbt and Snowflake expertise (or equivalent modern data stack). Experience with BI tools (Sigma, Tableau, Mode, Looker) and designing/analyzing experiments is required. Familiarity with credit, risk, or fintech data is a plus. The role requires comfort partnering with both technical and non-technical stakeholders.
