Onboarding Fraud Data Scientist

Matcha; Northern (KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive compensation

Equity package

Flexible PTO

Fully covered healthcare

Dependent coverage

Parental leave (20 weeks)

Job summary

Imprint is seeking a Data Scientist focused on Onboarding Fraud to own the modeling and analytics that power fraud and identity decisions from application submission through account opening.

You will partner with Fraud Strategy, Product, Engineering, Compliance, and Credit Strategy to improve onboarding fraud and KYC decisioning, build scalable policies, and monitor evolving fraud patterns.

Qualifications

• 5 to 8+ years of experience in data science, risk analytics, or a related quantitative field.
• Strong Python and SQL skills and ability to build models and transform data.
• Experience building predictive models for fraud, identity, KYC, AML, or related adversarial problems.
• Strong understanding of supervised ML, model validation, backtesting, calibration, feature engineering, and production monitoring.
• Deep understanding of statistical inference and experiment design, including A/B tests and causal measurement.
• Ability to evaluate decision systems using metrics like fraud capture, loss rate, false positives, and verification impact.
• Full-stack problem-solving: trace decisions from inputs to outcomes to find root causes.
• Comfort owning projects end-to-end and communicating complex analyses to technical and non-technical audiences.
• Excitement about AI-powered risk systems and tooling.

Responsibilities

• Own onboarding fraud decisioning across the full application journey including identity verification and KYC controls.
• Build, validate, deploy, and monitor models detecting identity theft, synthetic identity, and application abuse.
• Evaluate third-party fraud vendors by testing scores, lift, overlap, coverage, latency, and cost.
• Design and analyze A/B tests, shadow tests, holdouts, and champion/challenger strategies.
• Investigate emerging fraud patterns and translate findings into features, rules, and review strategies.
• Build monitoring and AI-powered workflows to detect model drift and data-quality issues.
• Collaborate with Fraud Ops, Product, Engineering, Compliance, and Credit Strategy to productionize changes.

Skills

Python

SQL

Fraud modeling

Experiment design

Model validation

End-to-end ownership

Communication

AI tooling

Tools

Snowflake

AWS

Dashboarding

Job description

Imprint is seeking a Data Scientist focused on Onboarding Fraud to own the modeling and analytics that power fraud and identity decisions from application submission through account opening.

You will partner with Fraud Strategy, Product, Engineering, Compliance, and Credit Strategy to improve onboarding fraud and KYC decisioning, build scalable policies, and monitor evolving fraud patterns.