Senior AI/ML Lead

Elder Research

$120K — $160K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in statistics, computer science, data science, or related fields.
  • 3+ years of experience in fraud detection or risk modeling.
  • Advanced expertise in machine learning and applied statistics.
  • Experience managing the full lifecycle of analytics models in production.
  • Strong background in predictive modeling and anomaly detection.
  • Proficient in SQL and Python for analytical programming.
  • Experience with large datasets in enterprise analytical environments.

Responsibilities

  • Lead machine learning and advanced analytics initiatives.
  • Develop and evaluate models for fraud and identity theft detection.
  • Manage the lifecycle of analytical models from development to monitoring.
  • Modernize existing analytical model portfolios effectively.
  • Integrate models into operational systems alongside data engineers.
  • Document methodologies and analytical findings thoroughly.
  • Engage with stakeholders during technical reviews and discussions.

Benefits

  • Hybrid work environment with onsite collaboration days.
  • Opportunity to work on impactful fraud prevention projects.
  • Access to advanced analytics tools and technologies.
  • Supportive culture focused on professional development.
  • Engagement in technical reviews and stakeholder discussions.
Full Job Description
Senior AI/ML Lead

General Information

Requisition # 682

Locations USA-VA-Arlington

Posting Date 03/20/2026

Security Clearance Required - ACTIVE IRS MBI

Remote Type Hybrid

Time Type Full time

Description & Requirements

We are seeking a Senior AI/ML Lead to drive advanced modeling and analytical approaches supporting fraud detection and identity theft analytics. This role provides technical leadership across the lifecycle of machine learning models used to detect risk, identify anomalous activity, and strengthen fraud prevention capabilities.
The ideal candidate brings deep technical expertise and experience deploying analytical models in production environments operating at enterprise scale.

Responsibilities include but are not limited to:
  • Provide technical leadership for machine learning and advanced analytics initiatives.
  • Design, develop, and evaluate models used to detect fraud, identity theft, and anomalous behavior.
  • Support the full lifecycle of analytical models, including development, validation, deployment, and monitoring.
  • Assess, refresh, consolidate, and modernize existing analytical model portfolios.
  • Apply machine learning, statistical modeling, and AI techniques to large-scale datasets.
  • Collaborate with data engineers and subject matter experts to integrate models into operational systems.
  • Document methodologies, model performance metrics, and analytical findings.
  • Support technical reviews, program briefings, and stakeholder discussions

Minimum Qualifications: (5 to 7 bullets max)
  • Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, data engineering, business, or social sciences
  • 3+ years of experience applying analytics to fraud detection, identity theft analytics, risk modeling, or financial crime detection.
  • Advanced experience in machine learning, applied statistics, data science, or artificial intelligence.
  • Demonstrated experience supporting full model lifecycle management in production analytics environments.
  • Expertise in predictive modeling, anomaly detection, and supervised and unsupervised machine learning techniques.
  • Strong experience working with large-scale datasets in distributed or enterprise analytical environments, including Databricks, PostgreSQL, or similar platforms.
  • Proficiency in SQL, Python, and related analytical programming languages.
  • Experience performing feature engineering, model evaluation, model monitoring, and analytical workflow automation.

Preferred Qualifications:
  • Advanced degree (MS) in analytics, computer science, data science, mathematics, statistics, engineering, management information systems, decision science, or related fields
  • Familiarity with tax administration or financial transaction environments, including regulatory or compliance-driven analytics.
  • Ability to translate complex analytical results into insights usable by operational and program stakeholders.
  • Strong documentation and communication skills for technical and executive audiences.

Clearance Requirements:
  • Must currently possess an IRS Public Trust clearance with Full Background Investigation

Physical Requirements:
  • Must be able to remain in a stationary position 50%
  • Needs to occasionally move about inside the office to access file cabinets, office machinery, etc.
  • Frequently communicates with co-workers, management, and customers, which may involve delivering presentations.
  • Must be able to exchange accurate information in these situations

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