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AI Transaction Monitoring Analyst

Jordan Lindqvist

Full-time · Job · Chicago

About the role

Our fraud detection models flag 800 transactions per day as potentially suspicious. Most of them aren't. As a transaction monitoring analyst, you'll investigate these alerts — reviewing transaction patterns, checking against known fraud typologies, and classifying each alert as genuine fraud, false positive, or escalation-required. Your classifications feed directly back into the detection models. Every false positive you correctly identify helps the model learn what legitimate transactions look like. Every confirmed fraud case strengthens the patterns the model watches for. You're the human in the loop that makes the ML system smarter over time. This is an analytical entry point into financial crime detection. You'll learn transaction analysis, fraud typologies, and the regulatory framework that governs suspicious activity reporting. Within a year, you'll understand payment fraud patterns well enough to design the detection rules yourself.

Responsibilities

  • Investigate 800+ daily flagged transactions for fraud classification
  • Classify alerts as confirmed fraud, false positive, or escalation-required
  • Document investigation findings for model feedback and compliance records
  • Identify emerging fraud patterns not captured by existing detection rules
  • Generate weekly reports on fraud trends and model performance

Requirements

  • Python and SQL proficiency for transaction data analysis
  • Strong analytical reasoning for pattern detection
  • Attention to detail for financial record review
  • Basic understanding of statistics for trend analysis
  • Interest in financial crime detection or compliance

Benefits

  • Fully remote — US Central time zone
  • Health insurance
  • Structured mentorship program
  • Career path into fraud analytics or ML engineering

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

data science & analytics

Skills

python sql pandas scikit-learn statistics

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