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AI Anti-Money Laundering Model Developer

Jordan Lindqvist

Full-time · Job · New_York

About the role

Banks file 4 million Suspicious Activity Reports per year in the US alone, and 95% of them are false positives generated by rule-based transaction monitoring systems. Each false positive costs $25-50 in analyst investigation time. Our ML models replace those rules with learned patterns, cutting false positive rates by 70% while catching more actual suspicious activity. The regulatory environment makes this uniquely challenging. Models must be explainable — regulators won't accept a black box that says "this transaction is suspicious" without showing why. You'll build models that balance detection performance with interpretability, generate evidence summaries that satisfy compliance officers, and maintain documentation that passes regulatory examination. This role sits at the intersection of ML engineering and financial compliance. You'll work with our model risk management team who validate every model before deployment, and our client-facing analysts who translate model outputs into regulatory filings. The ML team is six people; you'll be the most senior model developer.

Responsibilities

  • Develop ML models for transaction monitoring with high sensitivity and low false positive rates
  • Ensure model explainability sufficient for regulatory review
  • Generate evidence summaries that support analyst investigation workflows
  • Maintain model documentation for regulatory examination readiness
  • Collaborate with model risk management on validation and governance
  • Monitor deployed models for performance drift and recalibrate as needed

Requirements

  • 6+ years in ML with experience in financial crime, risk, or compliance domains
  • Deep understanding of classification under extreme class imbalance
  • Experience with explainable AI techniques: SHAP, LIME, or attention-based methods
  • Strong Python, SQL, and distributed computing skills
  • Knowledge of BSA/AML regulations and model risk management frameworks

Benefits

  • Fully remote with quarterly in-person team meetings
  • Competitive salary with annual performance bonus
  • Comprehensive health, dental, and vision
  • 401(k) with 5% match
  • $4,000 annual professional development budget

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch sql spark docker

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch sql spark docker statistics

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