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
Elder Research Inc., a wholly owned subsidiary of MANTECH international Corporation seeks a motivated, career and customer-oriented Senior AI/ML Lead to join our team in Arlington, VA. This is a hybrid position with several days onsite over the course of a month.
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:
- 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
About Elder Research, Inc - People Centered. Data Driven
Elder Research considers all qualified applicants for employment without regard to disability or veteran status or any other status protected under any federal, state, or local law or regulation.
If you need a reasonable accommodation to apply for a position with Elder Research, please email us at [email protected] and provide your name and contact information.
