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AI Card-Not-Present Fraud Scoring Engineer

William Bergmann

Full-time · Job · New_York

About the role

We process risk scoring for card-not-present transactions on behalf of mid-market e-commerce platforms handling millions of orders a month. In this role, you'll build and maintain the scoring models that flag suspicious online transactions in under 200 milliseconds, balancing fraud capture against false-positive rates our merchant clients hold us accountable for. Every basis point of model improvement translates directly into recovered merchant revenue, and your work will be reviewed monthly against client-reported chargeback outcomes.

Responsibilities

  • Maintain and improve real-time card-not-present fraud scoring models
  • Balance fraud capture rate against false-positive impact on merchants
  • Analyze chargeback outcomes to retrain models on a regular cadence
  • Collaborate with client success on merchant-specific tuning
  • Ensure scoring latency stays within SLA

Requirements

  • Experience building fraud or risk scoring models in production
  • Strong Python and SQL skills, comfortable with Spark at scale
  • Understanding of precision/recall tradeoffs under latency constraints
  • Experience with cloud-based model serving

Benefits

  • Remote position
  • Health, dental, and vision insurance
  • Performance bonus tied to chargeback reduction
  • 401k matching

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python sql scikit-learn spark aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python sql scikit-learn spark aws

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