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Kikoff
San Francisco
Source: Kikoff careers · View original posting
From Kikoff's posting. “We” and “our” refer to the employer.
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.
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.
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.
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.
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