Fraud Data Science Lead Job at ALOIS Solutions, Dallas, TX

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  • ALOIS Solutions
  • Dallas, TX

Job Description

What You’ll Do

  • Architect and lead fraud prevention strategies across financial products (e.g., onboarding, ATO, payments).
  • Design and optimize detection logic using platforms like ThreatMetrix , ensuring high fraud capture with minimal customer friction.
  • Perform deep analytics and uncover emerging fraud patterns in structured and unstructured data.
  • Monitor fraud KPIs such as detection rate, false positives, and loss capture to inform strategic pivots.
  • Collaborate cross-functionally with Product, Engineering, Risk, and Compliance to operationalize insights.
  • Lead incident reviews and present strategic recommendations to senior stakeholders.
  • Stay ahead of the curve by tracking fraud trends and regulatory shifts.

What You Bring

  • 7+ years in fraud strategy, analytics, or data science—preferably in retail banking or card products .
  • Expert-level proficiency in SQL and Python ; familiarity with tools like Hive, Spark, AWS SageMaker .
  • Strong experience in fraud detection platforms ( LexisNexis, Actimize , etc.), especially ThreatMetrix .
  • Solid grasp of statistical modeling and predictive analytics.
  • Confident communicator with proven success in cross-functional, client-facing environments.
  • Strategic mindset with hands-on delivery capabilities.

Bonus Points:

  • Experience with ML-based fraud modeling.
  • Consulting background in fraud strategy.
  • Familiarity with fraud loss appetite frameworks.

Join a team where your insights influence millions, your strategies stop fraud cold, and your leadership pushes the boundaries of risk intelligence.

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