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AI Wire Transfer Fraud Detection Engineer

William Bergmann

Full-time · Job · New_York

About the role

Wire transfers move $5 trillion per day globally. When a fraudulent wire goes through, the money is often irreversible within hours. Our detection system evaluates every outgoing wire transfer in real time — 140ms average decision time — scoring it against the sender's behavioral baseline, beneficiary risk profile, and network-level anomaly signals. The class imbalance is extreme: 1 fraudulent wire per 50,000 legitimate ones. A model that flags 0.1% of transactions generates 50 false alerts for every true positive — far too noisy for investigation teams. You'll push the precision-recall frontier by engineering features that capture the subtle differences between authorized unusual transfers (a CFO wiring to a new supplier) and social engineering attacks (a compromised email instructing a wire to a mule account). The financial crime ML team is seven engineers. You'll be the senior model developer for wire fraud specifically, with access to labeled datasets spanning 3 years of wire transfer activity across 15 financial institutions.

Responsibilities

  • Develop real-time fraud scoring models for wire transfer evaluation
  • Engineer features distinguishing authorized unusual transfers from fraud
  • Optimize precision-recall under extreme class imbalance
  • Build model explainability for investigator decision support
  • Validate models against labeled fraud cases and regulatory scenarios
  • Collaborate with financial crime investigators on detection requirements

Requirements

  • 5+ years in ML with financial crime or fraud detection experience
  • Deep expertise in classification under extreme class imbalance
  • Experience with real-time model serving at sub-200ms latency
  • Strong Python, PyTorch, and SQL skills
  • Understanding of wire transfer operations and fraud typologies

Benefits

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

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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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