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Data Scientist, Grant

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: RiseMe
Full Time position
Listed on 2026-09-28
Job specializations:
  • IT/Tech
    Data Analyst, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 265000 - 306000 USD Yearly USD 265000.00 306000.00 YEAR
Job Description & How to Apply Below

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 Grant

Grant is Kikoff's fastest growing business line. It started with earned wage access, solving the most common and most painful problem in consumer finance: short-term liquidity. Gas to get to work, an unexpected bill, groceries before the next paycheck. We give people fast, fair access to earned wages without the fees the industry has normalized, and we do it with a profitable business model.

Since launching to the public at the start of 2025, Grant has grown from thousands to 900k+ active subscribers and has disbursed and recollected over $325M in cash advances. EWA is the core, and several new products are underway on top of it.

Grant runs as its own business inside Kikoff, with a business lead and dedicated product, engineering, design, and marketing leads.

About the Grant data science team

Our job is to make sure every Grant 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 team of three data scientists within Kikoff's Data organization, embedded full time with Grant. Each of us leads the data work for a product area and all of us take part in Grant-level roadmap and objective setting with Grant's business lead and the product, engineering, design, and marketing leads.

About the role

You'd be the fourth Data Scientist focused on the Grant business, and part of a larger Kikoff wide Data team. You'll take on a product area within Grant as its data lead, working day to day with the leads for that area, and you'll bring a staff-level view to the Grant-wide conversations on where the business goes next.

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, not just Grant. 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 Grant 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 product area (acquisition, activation, usage, repayment, losses, unit economics) and contribute to the Grant-wide measurement framework alongside the other data scientists on the team.
  • Own product experimentation for your area: design, guardrails, analysis, and the recommendation on rollouts and policy changes (eligibility, limits, pricing), including changes where clean randomization isn't available.
  • Build and evaluate models where they're the right tool: proof-of-concept and challenger models, offline evaluation, threshold and policy decisions, and production monitoring with engineering. The ML platform and production model lifecycle sit with our ML engineering team; how data and engineering divide that work is still evolving and you'll have a voice in it.
  • Partner with Grant's business lead and the area leads on roadmap and objectives: which bets, what a win looks like, and what we'd need to see to stop.
  • As a staff data scientist, contribute to technical direction and best practices for data science across Kikoff, not just Grant: how we do experimentation, how we use AI tooling, how we review each other's work.
Minimum…
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