Data Scientist (Onboarding Fraud)

Location: Remote within the United States; New York City or San Francisco

Salary: $170,000–$200,000 per year plus equity

Company

hirify.global builds co-branded credit-card programs and embedded financial products using payments infrastructure, intelligent underwriting, and customer data.

What you will do

• Own onboarding fraud decisioning across identity verification, KYC controls, application fraud models, policy rules, verification waterfalls, and manual review.
• Build, validate, deploy, and monitor models detecting identity theft, synthetic identity, first-party fraud, and coordinated application abuse.
• Evaluate third-party fraud and identity vendors using lift, coverage, stability, latency, cost, and overlap analysis.
• Design A/B tests, shadow tests, holdouts, and champion/challenger strategies while balancing fraud losses, approval rates, false positives, verification friction, and operational workload.
• Investigate emerging fraud patterns, decision misses, model drift, population shifts, vendor degradation, and data-quality issues.
• Partner with Fraud Operations, Product, Engineering, Compliance, Credit Strategy, senior leadership, and external partners to productionize changes and measure business impact.

Requirements

• 5–8+ years of experience in data science, risk analytics, or a related quantitative field.
• Strong Python and SQL skills, including modeling, data transformation, and dataset creation from complex financial data.
• Experience building predictive models for fraud, identity, KYC, AML, credit risk, trust and safety, or other adversarial classification problems.
• Strong knowledge of supervised machine learning, model validation, backtesting, calibration, feature engineering, statistical inference, and production monitoring.
• Experience with experiment design, A/B testing, holdouts, champion/challenger testing, causal measurement, and decision-system tradeoff analysis.
• Ability to use AI tools for analysis, investigation, feature development, documentation, monitoring, and AI-powered risk systems.

Nice to have

• Experience with application fraud, identity theft, synthetic identity, fraud rings, KYC, CIP, identity verification, or document verification.
• Experience with device intelligence, behavioral signals, consortium data, credit bureau data, graph methods, anomaly detection, or weakly supervised methods.
• Experience evaluating fraud vendors, real-time scoring, decision engines, rules platforms, APIs, or production ML systems.
• Experience with fraud operations, credit-card underwriting, consumer lending, or regulated financial products.

Culture & Benefits

• Competitive compensation and equity package.
• Flexible paid time off.
• Fully covered healthcare, including dependent coverage, with access to One Medical and an FSA option.
• 20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents.
• Choice of work computer and access to technology across business units.