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.
As a Operations Data Scientist at Kikoff, you work closely with cross functional teams including Customer Operations, Product Operations, Product, Engineering, and Data Engineering to make our operations smarter, faster, and more customer-centric. Operations sits at the front line of our customer experience, and you will turn the massive amount of unstructured and structured data generated there into decisions, workflows, and tools that improve both agent and customer outcomes.
This is a high-ownership role. We are looking for someone with an owner mindset who proactively seeks out opportunities to apply a sharper technical and analytical lens to how Ops runs. You will define your own roadmap as often as you execute against someone else's.
Your responsibilities include:
- Ops AI ownership: Own and evolve Ops AI, our AI agent that helps Ops investigate customer issues and pull accurate data. Design and iterate on the agent's harness (SQL library, memory, context, skills, tools, guardrails), continuously improve its accuracy and expand its use cases as new workflows emerge.
- Ops Analytics and Measurement: Use data to shape how Ops runs. Define core Ops metrics, build self-serve dashboards and turn unstructured customer data into insights, design and run experiments to turn ops insights into product changes
- Cross-Functional Collaboration: Partner with Product Ops, CX Ops, and Operation Agents to translate data into decisions, workflows, and tooling that improve customer and agent outcomes.
- Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
- Expert knowledge of SQL
- Enthusiasm and comfort using AI tools (eg. LLMs, Claude Code) in analytics
- Strong verbal and written communication skills
- A humble collaborative can-do attitude, bias to action, and a hunger to apply a technical lens to messy, ambiguous operational problems
- Solid understanding of statistical analysis, experimentation design, and common ML techniques
- 1-2 years of data science experience
- Enthusiasm and comfort with using AI in analytics or for fintech problems
- Experience with Machine Learning especially in a production environment
Equal Employment Opportunity Statement
Kikoff Inc. is an equal opportunity employer. We are committed to complying with all federal, state, and local laws providing equal employment opportunities and considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Please reference the following for more information.
Kikoff San Francisco, California, USA Office
We’re headquartered in the Financial District of San Francisco where public transit is just a short walk away at Embarcadero Station.
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
