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AI Fraud Detection Specialist

Mendra Intelligence

Remote · $130k – $160k / year · Contract · Posted 5 months ago

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About the role

Payment fraud cost our clients $47M last year. They've tried rule-based systems. They've tried off-the-shelf solutions. Now they want custom ML models trained on their specific transaction patterns, and they're willing to pay for it. This is a 9-month contract to build fraud detection models for 3 financial services clients. Each engagement follows the same arc: audit their transaction data, engineer features from payment flows, train and evaluate detection models, and deploy them behind their existing risk scoring APIs. We need someone who's built fraud models before and understands the domain — class imbalance, adversarial drift, real-time scoring constraints, and the constant tension between false positives and false negatives. If you've lived in this world, the work will feel familiar but never boring.

Fully remote.

Responsibilities

  • Build custom fraud detection models for 3 financial services clients
  • Engineer features from payment transaction streams and user behavior data
  • Handle extreme class imbalance with appropriate sampling and loss strategies
  • Deploy models behind existing risk scoring APIs with latency constraints
  • Deliver model performance reports and retraining recommendations per client

Requirements

  • 5+ years in ML with fraud detection or financial services experience
  • Strong PyTorch and scikit-learn skills
  • Experience with Spark for large-scale feature engineering
  • Deep understanding of class imbalance, adversarial drift, and real-time scoring
  • Ability to manage independent client engagements and deliver on schedule

Benefits

  • 9-month contract with renewal option
  • Fully remote
  • Premium contract rate
  • Diverse client exposure in financial services

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Job Type

Contract

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

AI & Machine Learning Engineers Data Science & Analytics

Skills

python pytorch scikit-learn sql spark pandas statistics

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