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AI Synthetic Identity Detection Engineer

William Bergmann

Full-time · Job · New_York

About the role

Synthetic identity fraud is the fastest-growing financial crime in the US — fraudsters combine real and fabricated identity elements to create personas that pass traditional verification. A real Social Security number paired with a fake name and a manufactured credit history can open accounts, build credit, and bust out for $100K+ before anyone notices the identity doesn't belong to a real person. Our detection system identifies synthetic identities by analyzing patterns that real people don't exhibit: credit history inconsistencies, address velocity anomalies, device fingerprint mismatches, and application behavior that follows known fraud playbooks. You'll build the ensemble model that scores new account applications and existing accounts for synthetic identity risk. The identity fraud team is six engineers. You'll be the senior model developer, working with a fraud investigator who provides case-level insight into how synthetic identities are constructed and a data partnerships manager who sources the external data feeds that make detection possible.

Responsibilities

  • Build synthetic identity detection models for account application scoring
  • Design features capturing identity construction patterns and inconsistencies
  • Engineer cross-source verification signals from credit, address, and device data
  • Handle extreme class imbalance with novel synthetic identities as positive class
  • Validate detection against confirmed synthetic identity fraud cases
  • Collaborate with fraud investigators on emerging construction techniques

Requirements

  • 5+ years in ML with identity verification or fraud detection experience
  • Experience with entity resolution and cross-source identity matching
  • Strong Python, PyTorch, and distributed computing skills
  • Understanding of credit bureau data and identity verification systems
  • Knowledge of synthetic identity fraud typologies and detection challenges

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 budget

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch sql spark statistics

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Job Type

Full-time

Level

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Language

English

Salary Range

$130k – $160k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch sql spark statistics docker

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