Data Scientist

San Francisco, United StatesOn-site

Requirements

Kikoff: A FinTech Unicorn Powering Financial Progress with AI
With innovative technology and AI, we simplify credit building, reduce debt, and expand access to financial opportunities to those who need them the most.
We value extreme ownership, clear communication, a strong sense of craftsmanship, and the desire to create lasting work and work relationships.
As a Data Scientist at Kikoff, you work closely with cross functional teams incl.
Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field •
Expert knowledge of SQL and experience with Python •
Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees •

We're a profitable, high growth FinTech unicorn serving millions of people, many of whom are building credit or navigating life paycheck to paycheck.
Base Range $160,000 — $260,000 USD
Equal Employment Opportunity Statement

At Kikoff, our mission is to provide radically affordable financial tools to help consumers achieve financial security.
Founded in 2019, Kikoff is headquartered in San Francisco and backed by top-tier VC investors and NBA star Stephen Curry. 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.
Yes, you can build an exciting business AND have real-life real-customer impact.
Product, Engineering, Data Engineering, Marketing, Operation.
By applying your technical skills, analytical mindset, and product intuition, you will help our customers improve their financial security.
You will use data to identify and solve product development’s biggest challenges.
Product leadership: use data to shape product development, quantify new opportunities, set goals, identify upcoming challenges, and ensure the products we build bring value to our customers. •
Analytics: develop hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them. •
Communication and influence: convince and influence your partners by telling clear data stories.