Data Scientist, Credit Risk

Salary: $140K - $180K Employment Type: Full-Time Location Type: Remote

Who We Are

Imprint is reimagining co-branded credit cards and financial products to be smarter, more rewarding, and truly brand-first. We partner with companies like H-E-B, Turkish Airlines, Brooks Brothers, and Eddie Bauer to launch modern credit programs that deepen loyalty, unlock savings, and drive growth. Our platform combines advanced payments infrastructure, intelligent underwriting, and seamless UX to help brands offer powerful financial products—without becoming a bank.

Co-branded cards account for over $300 billion in U.S. annual spend—but most are still powered by legacy banks. Imprint is the modern alternative: flexible, tech-forward, and built for today’s consumer. Backed by Kleiner Perkins, Thrive Capital, and Khosla Ventures, we’re building a world-class team to redefine how people pay—and how brands grow. If you want to work fast, solve hard problems, and make a real impact, we’d love to meet you.

The Role

Join our mission-driven credit card startup as a Data Scientist on the Credit Risk team. You’ll play a pivotal role in building the analytical and modeling foundation that powers smarter, faster, and safer credit decisions. Your expertise will guide the development of robust underwriting models, fraud detection systems, and credit policies that balance growth with risk mitigation, enabling us to scale responsibly while delivering innovative credit products.

The Team

The Credit Risk & Analytics team is central to Imprint's success, responsible for enabling sustainable growth by managing the inherent risks in lending. We build and refine the machine learning models and data-driven strategies that underpin our credit decisions, from underwriting new applicants to managing portfolio risk. We leverage diverse data sources and advanced analytical techniques to optimize credit policies, minimize losses, and ensure regulatory compliance, all while delivering a seamless experience for our partners and customers.

What You’ll Do

• Develop & Enhance Credit Models: Design, develop, implement, and maintain advanced statistical and machine learning models for core credit risk areas (underwriting, fraud detection, credit line assignment, loss forecasting, portfolio management), leveraging traditional credit bureau data and alternative data sources (e.g., bank transactions, specialty bureaus).
• Data Analysis & Insights: Analyze large, complex datasets to identify trends, patterns, and actionable insights that inform credit policy, risk appetite frameworks, and overall business strategy.
• Experimentation & Optimization: Design, execute, and evaluate experiments (including A/B testing and policy change impact analysis) to measure and continuously improve the effectiveness of credit risk strategies and models.
• Monitor & Validate Performance: Continuously monitor, validate, and enhance the performance of existing risk models, ensuring robust documentation, adherence to model governance standards, regulatory compliance, and timely updates in response to portfolio performance and market changes.
• Cross-Functional Collaboration: Work closely with Product, Engineering, Credit, Operations, Finance, Legal, and Compliance teams to seamlessly integrate data science solutions, deploy models into production, and support end-to-end project delivery.
• Innovation & Research: Lead the identification, evaluation, and integration of new data sources and modeling techniques, including emerging ML/AI approaches, to continuously improve risk prediction and decision-making capabilities.
• Strategy Support: Support pricing and credit limit strategies through quantitative analysis of risk-adjusted returns and loss forecasting.
• Communication: Present complex analytical findings, model results, and strategic recommendations to technical and non-technical stakeholders, including senior management, using clear narratives and effective visualizations.

What We Look For

• Experience: 4+