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Alloy

Identity verification and KYC/AML compliance platform

Senior Machine Learning Engineer

Applied Machine LearningUpdated on Nov 12
Full-timeNew York, NY, USA$159k - $230k

About the Job

Requirements

  • Have 8 or more years as an individual contributor in Applied Fraud Research, Data Science, or Machine Learning, with a proven track record in a solutions or client-facing capacity.
  • Have expertise working with highly imbalanced datasets and building production-grade machine learning models, with specific interest in tree-based models.
  • Have advanced proficiency in Python and SQL.
  • Be able to process and analyze data at scale, including billions of records.
  • Have experience developing metrics and dashboards.
  • Be able to communicate findings effectively to technical and nontechnical audiences.
  • Have experience in a highly analytical role in fast-paced environments.
  • Be local to Greater New York City.

Responsibilities

  • Contribute to the design, training, and evaluation of machine learning models that power fraud detection capabilities.
  • Develop testing plans, metrics, and performance reports, and translate findings into actionable recommendations.
  • Support production machine learning workflows, including feature generation, model training, and monitoring, to ensure models remain accurate and reliable at scale.
  • Document findings and communicate insights to internal teams, contributing to shared learning and continuous improvement.
  • Maintain up-to-date model documentation and support model governance processes to ensure transparency and compliance.
  • Stay current with industry trends in applied machine learning and fraud detection.
  • Partner directly with customers to drive strong outcomes from fraud studies.

Desired Qualifications

  • Have previous experience in financial fraud detection.
  • Have an advanced degree (Master's or PhD) in a quantitative field.
  • Have experience managing the end-to-end lifecycle of a technical pilot or Proof of Concept.
  • Have experience with business intelligence tools such as Looker.
  • Have experience modeling on graph structures.

About the Company

Alloy

Identity verification and KYC/AML compliance platform

Alloy provides identity verification and compliance solutions for financial institutions. It offers a platform that integrates with multiple data sources to verify the identities of individuals and businesses, helping banks, credit unions, and fintechs streamline customer onboarding while meeting regulatory requirements like KYC and AML. The product uses machine learning and AI to assess risk, validate identities, and detect potential fraud, enabling clients to reduce fraud, ensure compliance, and improve the onboarding experience. Alloy differentiates itself by focusing on bank and fintech ecosystems with data-source integrations, ML-driven risk assessment, and a subscription-based platform that supports ongoing compliance and onboarding needs. The company’s goal is to help financial institutions prevent fraud, stay compliant with regulations, and provide a smooth, efficient onboarding process for customers.

Company size
201-500
Company stage
Late Stage VC
Total funding
$216.7M
Headquarters
New York City, New York
Founded
2015

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