About this role
Imprint is seeking an experienced remote Data Scientist, Risk to own and improve the top-of-funnel credit decisioning pipeline for its modern financial products. This full-time role suits a quantitative expert with a background in fintech who wants to balance growth with responsible risk management.
Role Overview
The Risk team at Imprint is responsible for making smarter, faster credit decisions that balance growth with responsible risk management. As a Data Scientist, Risk, you will own the modeling powering Imprint's top-of-funnel credit decisioning—from application intake through approval—across every acquisition channel. Your primary focus will be improving approval rates while maintaining credit quality by building better underwriting models, designing policy experiments, and uncovering safe segments for credit expansion.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
About the Company
Imprint helps the world's best brands grow the lifetime value of their customers by rebuilding co-branded credit cards to be smarter, more rewarding, and brand-first. Backed by investors like Kleiner Perkins, Thrive Capital, Ribbit, and Khosla Ventures, Imprint combines advanced payments infrastructure, intelligent underwriting, and deep customer data.
How to Apply
Candidates should visit the official Imprint careers page to apply for this remote position.
Skills and tech stack
Questions candidates ask
What is the salary range for the Data Scientist, Risk role?
The salary range for this position is $170,000 to $200,000 USD per year.
Is this position remote?
Yes, this is a fully remote position.
What technical skills are required?
Candidates must have strong Python and SQL skills, along with experience in data science, risk analytics, or predictive modeling in a regulated environment.
What level of experience is expected?
The role requires 5 to 8+ years of experience in data science, risk analytics, or a related quantitative field.
What tools and technologies are used in the stack?
The technology stack includes Python, SQL, Snowflake for data warehousing, AWS infrastructure, and various dashboarding and monitoring tools.
