Senior Marketing Data Scientist at Kikoff

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

11 Jun, 26

Salary

260000.0

Posted On

13 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Causal Inference, Experimentation Design, Attribution Modeling, Marketing Mix Models (MMM), Incrementality Testing, Forecasting, Anomaly Detection, Data Science, Analytics, Paid Media Channels, Growth

Industry

Software Development

Description

Kikoff: A FinTech Unicorn Powering Financial Progress with AI At Kikoff, our mission is to provide radically affordable financial tools to help consumers achieve financial security. We're a profitable, high growth FinTech unicorn serving millions of people, many of whom are building credit or navigating life paycheck to paycheck. With innovative technology and AI, we simplify credit building, reduce debt, and expand access to financial opportunities to those who need them the most. 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. 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. The Role You'll be the analytical engine behind Kikoff's paid media channels — owning diagnostics, experimentation, and measurement that inform tens of millions in spend decisions. This is not a reporting role. You'll work at the intersection of causal inference, channel economics, and attribution, partnering closely with Growth leadership and our Head of Marketing Data Science. Responsibilities Own marketing measurement and attribution frameworks across paid channels (e.g., Google, Meta, TikTok, TV), including experimentation, incrementality testing, and attribution modeling to quantify channel effectiveness and guide budget allocation Build and operationalize scalable measurement solutions such as Marketing Mix Models (MMM), channel-level performance diagnostics, and CAC/LTV forecasting to support growth decisions and optimize marketing spend Design and execute 5–6 incrementality tests annually, including power analysis, monitoring, and executive readouts Reconcile platform-reported metrics with internal attribution models and MMM (Northbeam) outputs Build and maintain real-time anomaly detection across acquisition channels Support brand test design and translate NPS/sentiment signals into growth insights Qualifications 4+ years in data science or analytics, with at least 2 years in marketing or growth contexts Expert SQL and strong Python; deep familiarity with experimentation design and causal inference methods Experience with paid media channels and platform-level attribution mechanics Comfort with MMM outputs and reconciling econometric findings with channel data Strong communicator — able to translate statistical results into clear recommendations for non-technical stakeholders Bachelor's or advanced degree in a quantitative discipline Bonus Points Hands-on experience with incrementality frameworks (geo-based, time-based, ghost ads) Familiarity with Northbeam, Rockerbox, or similar attribution tooling Background in fintech, consumer lending, or subscription growth Base Range $160,000—$260,000 USD Location: Hybrid, 3 days onsite in San Francisco, CA. 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.

Responsibilities

The role involves owning marketing measurement and attribution frameworks across paid channels, including experimentation and modeling to quantify channel effectiveness and guide budget allocation. Responsibilities also include building and operationalizing scalable measurement solutions like MMMs and CAC/LTV forecasting to support growth decisions.