AI-Driven Risk Data Scientist — Credit Underwriting & Growth

Imprint; Northern, New York (KY, NY); Hybrid; USD 130,000 - 210,000; Full time

Benefits offered by this job

Competitive compensation

Equity packages

Flexible PTO

Healthcare coverage

One Medical access

FSA option

Parental leave

Job summary

Imprint is seeking a Data Scientist, Risk to own and evolve the modeling powering top-of-funnel credit decisioning across multiple channels. You will build and refine underwriting, segmentation, and policy experiments to balance growth with credit quality.

You will partner with Credit Strategy, Product, Engineering, and Marketing to drive channel performance, experiment design, and AI-powered monitoring, aiming to improve approval rates and LTV while controlling risk.

Qualifications

• 5 to 8+ years of experience in data science, risk analytics, or a related quantitative field, ideally at a high-growth startup or fintech
• Strong Python and SQL skills, with the ability to build models, transform raw data, and create custom datasets from complex financial data
• Experience building credit risk or targeting models (scorecards, underwriting models, segmentation) or similar predictive modeling in a regulated environment
• Deep understanding of statistical inference, experimentation design, and causal analysis, with the ability to disentangle policy impact from population shifts and channel mix changes
• Comfort with AI tools and AI-native workflows; you actively use tools like Claude, Copilot, or similar to accelerate your work and are excited to build AI-powered analytical systems
• Full-stack problem-solving orientation: you dive into messy data, trace a decline to its root cause, and question assumptions in pursuit of a better answer
• Ability to present complex findings clearly to technical and non-technical audiences, including senior leadership and external partner stakeholders
• Comfort owning projects end-to-end in a fast-moving startup environment with limited scaffolding, collaborating cross-functionally with Policy, Strategy, Product, and Engineering

Responsibilities

• Own and improve the full top-of-funnel credit decisioning pipeline: application scoring, policy rules, decline waterfalls, and approval rate optimization across direct affiliates, invitation-to-apply, direct mail, paid social, instant prescreens, and on-site applications
• Build and iterate on underwriting, targeting, and segmentation models that expand safe approvals and improve channel-level acquisition quality
• Design and analyze A/B tests and champion/challenger experiments on credit policies, establishing a test-and-learn cadence with structured readouts on both acquisition and credit performance
• Build channel-level performance models that connect application volume to downstream economics: approval rates, expected losses, LTV, CAC, and contribution profit
• Design and build agentic workflows and AI-powered monitoring systems that autonomously detect approval rate anomalies, diagnose score drift and population mix changes, and recommend policy adjustments
• Partner directly with Credit Strategy, Product, Engineering, and Marketing to develop targeting criteria and risk frameworks for new and emerging acquisition channels
• Build segmentation frameworks to identify underserved populations where credit access can be responsibly expanded

Skills

Python

SQL

Credit risk models

Segmentation

Experiment design

Causal analysis

AI tooling

Stakeholder communication

Tools

Snowflake

AWS

Job description

Imprint is seeking a Data Scientist, Risk to own and evolve the modeling powering top-of-funnel credit decisioning across multiple channels. You will build and refine underwriting, segmentation, and policy experiments to balance growth with credit quality.

You will partner with Credit Strategy, Product, Engineering, and Marketing to drive channel performance, experiment design, and AI-powered monitoring, aiming to improve approval rates and LTV while controlling risk.