Sr Staff Data Scientist, New Verticals

<div class="content-intro"><p>Flex is a growth-stage, NYC headquartered FinTech company that is building the payment layer for life's essential bills, giving households one place to see, split, and pay their bills around how they live and get paid. By offering greater choice over how and when payments are made and allowing eligible on time payments to help build a positive credit history, Flex puts households back in control of their cash flow.</p> <p>That work brings together people with different perspectives who challenge the status quo and take ownership of solving difficult problems. For you, that means doing the best work of your career next to people who make you better, and together bringing ideas to life that make a real impact for the people we serve.</p></div><p>Flex is expanding to offer a consumer bill management platform: a hub where users manage both recurring and one-off bills, align payments with their cash flow, and build credit along the way. As we move from a pilot to broader GTM, we're looking for someone who can operate as both the builder of our data foundation and the analyst who turns that data into decisions.</p> <p>This role will work closely with both business leadership and the core data team to focus on modeling data, digging into consumer behavior, pricing and credit dynamics, and setting the standards the rest of the team builds on.</p> <h4><strong>What you'll do</strong></h4> <ul> <li>Build and maintain the core data models (dbt/Snowflake) that power reporting, experimentation, and ML/credit risk use cases</li> <li>Analyze consumer bill payment behavior timing, splitting, delinquency, credit-building outcomes to identify what's working in the pilot and what needs to change</li> <li>Partner closely with Product and Engineering to instrument new features (e.g. bill splitting, smart scheduling, credit-building) so we can measure adoption and impact from day one</li> <li>Design and analyze experiments that test pricing, credit terms, and product flows, establishing causal links between changes and outcomes</li> <li>Create dashboards and self-serve tools that let Product, Risk, and GTM teams track Control Center's pilot-to-scale metrics without needing to come back to Analytics for every question</li> <li>Champion data quality, consistent terminology, and documentation as data footprint grows from pilot to full launch</li> <li>Set technical direction for how Control Center's data models and pipelines scale as new billers, partners, and product surfaces come online; mentor other analysts/engineers and raise the technical bar across the team</li> </ul> <h4><strong>Key qualifications</strong></h4> <ul> <li>7+ years of experience spanning analytics engineering and data science/