Data Scientist, Fraud Risk
New
I
ImprintFintech
RemoteFull-TimeSenior
Salary$170K - $200K; $170K – $200K • Offers Equity
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Job Details
- Experience
- 5 to 8+ years
- Required Skills
- PythonSQLMachine Learning
Requirements
- 5 to 8+ years of experience in data science, risk analytics, or a related quantitative field.
- Strong Python and SQL skills for modeling, data transformation, and custom dataset creation.
- Proven experience building and evaluating predictive models for fraud, identity, KYC, AML, or credit risk.
- Deep understanding of supervised machine learning, model validation, backtesting, and production monitoring.
- Strong statistical inference and experiment design skills, including A/B testing and causal measurement.
- Ability to evaluate decision systems using metrics like fraud capture, loss rate, and false-positive rate.
- Full-stack problem-solving orientation with the ability to trace decisions through raw inputs and policy rules.
- Experience owning projects end-to-end from problem definition to business impact measurement.
- Excellent communication skills for translating analytical findings to technical and non-technical stakeholders.
- Comfort using AI tools to accelerate analysis, documentation, and feature development.
Responsibilities
- Own and improve 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 coordinated application abuse.
- Evaluate third-party fraud and identity vendors by measuring incremental lift, stability, and cost.
- Design and analyze A/B tests, shadow tests, and champion/challenger strategies to balance fraud loss and approval rates.
- Investigate emerging fraud patterns by combining application outcomes with operational feedback to develop new controls.
- Build AI-powered workflows to detect model drift, data quality issues, and evolving attack patterns.
- Partner with Product, Engineering, Compliance, and Fraud Operations to productionize changes and communicate impact to leadership.
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