Senior Data Scientist

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About the role

Kikoff: The Fintech Powering Financial Security at Scale Kikoff is a profitable, pre-IPO fintech company on a mission to empower everyone to achieve financial security. With record revenue growth in 2025 and a unicorn valuation, we've built a suite of products that help millions of people build credit, access liquidity, and save money. We're scaling fast. Join us if you want to build something meaningful and help millions of people move forward financially. Why Kikoff: This is a consumer fintech startup, and you will be working with serial entrepreneurs who have built strong consumer brands and innovative products. We value extreme ownership, clear communication, a strong sense of craftsmanship, and the desire to create lasting work and work relationships. Yes, you can build an exciting business AND have real-life real-customer impact. About the Kikoff data science team Our job is to make sure every Kikoff product does three things: makes a clear and compelling promise to the customer, delivers on that promise reliably over time, and turns that durable value into a business healthy enough to fund the next product, in a way customers would agree is fair. Every metric we define, experiment we run, and model we build should trace back to one of those three. We're a Data organization of roughly 20 people across product data science, marketing data science, and data engineering. This role sits with the data scientists embedded in Kikoff's core credit-building products, working alongside a Marketing DS partner who owns acquisition measurement and a data engineering team that owns the shared tooling underneath all of us. You'll have people to learn from and people to bring along. About the role You'll take on a product area within core Kikoff as its data lead, working day to day with the product, engineering, design, and lifecycle marketing leads for that area, and you'll sit in the Kikoff-wide conversations on roadmap and objectives. Two things we're asking of this hire beyond the product area. First, help set technical direction and best practices for data science across Kikoff: how we do experimentation, how we evaluate AI products, how we review each other's work. Second, help define how we work as AI agents become a core part of the analysis loop, from exploration to pipelines to experiment readouts. We're actively rebuilding our workflow around this and want someone who has opinions. What you'll do • Lead the data work for a core Kikoff product area: set the questions worth answering, build the evidence, and drive what happens next. Sometimes the right call is not to act on a finding, and you'll make that case too. • Define and maintain the measurement system for your area across the whole customer journey (activation, engagement, credit outcomes, retention, revenue, unit economics), and contribute to the Kikoff-wide measurement framework alongside the other data scientists on the team. Where acquisition intersects with what you own, you'll work it jointly with Marketing DS rather than around them. • Own product experimentation for your area: design, guardrails, analysis, and the recommendation on rollouts, including the cases where a holdout isn't clean or the effect you care about (a customer's score) moves on its own schedule. • For AI product surfaces, own evaluation: decide what "good" means in checkable terms, build and validate automated scorers against human judgment, and turn what you find in real conversations into regression tests so the product can't quietly get worse. Keep the loop between error analysis and the eval set closed. • Build and evaluate models where they're the right tool: proof-of-concept and challenger models, offline evaluation, threshold decisions, and production monitoring with engineeri

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