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AI Legal Billing Anomaly Detection Engineer

Emma Garcia

Contract · Job · Chicago

About the role

Law firm invoices routinely get padded with duplicate time entries and rate mismatches that nobody catches until a client's general counsel flags it months later. We're building a model that flags these anomalies automatically before an invoice ever leaves the firm, comparing entries against historical billing patterns and matter budgets. You'll build the anomaly scoring pipeline on top of our existing billing data, working closely with the two engineers who own our financial intelligence stack. Small team, fast iteration — a flagged anomaly this week should be catching real dollars by next week, not next quarter.

Responsibilities

  • Build anomaly scoring models over historical legal billing data
  • Ship detection rules for duplicate entries and rate mismatches
  • Validate flagged anomalies against real client billing disputes
  • Iterate quickly with the financial intelligence engineering team

Requirements

  • 2+ years building anomaly detection or fraud scoring systems
  • Strong SQL and scikit-learn skills
  • Comfortable working with financial or billing datasets

Benefits

  • Contract engagement with possibility of extension
  • Remote-first, async-friendly schedule
  • Direct access to the founding engineering team

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Categories

data science & analytics

Skills

python sql scikit-learn statistics

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Job Type

Contract

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

data science & analytics

Skills

python sql scikit-learn statistics

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