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Fraud Detection Machine Learning Jobs in Silver Spring, MD

Elder Research

Senior AI/ML Lead

Arlington, VA · On-site

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 ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

  • Medical

  • Dental

  • Vision

  • PTO

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Develop and improve classification systems for safety, security, abuse detection, and intelligence ...

Ardent

Senior Cybersecurity Program Manager

Washington, DC · On-site

$131K - $131K/yr

  • Medical

  • PTO

Support implementation of fraud analytics strategies, machine learning initiatives, and data-driven fraud detection methodologies. * Ensure timely coordination of fraud incidents, mitigation efforts ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

  • Medical

  • Dental

  • Vision

  • PTO

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Develop and improve classification systems for safety, security, abuse detection, and intelligence ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

  • Medical

  • Dental

  • Vision

  • PTO

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Develop and improve classification systems for safety, security, abuse detection, and intelligence ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

  • Medical

  • Dental

  • Vision

  • PTO

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Develop and improve classification systems for safety, security, abuse detection, and intelligence ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Job Number: R0245170 Machine Learning Engineer The Opportunity: As an experienced AI and ML ... We reserve the right to take your picture to verify your identity and prevent fraud. Candidate AI ...

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All JobsFraud Detection Machine Learning JobsFraud Detection Machine Learning Jobs in Silver Spring, MD

Fraud Detection Machine Learning information

See Silver Spring, MD salary details

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How much do fraud detection machine learning jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for fraud detection machine learning in Silver Spring, MD is $18.66, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $19.90 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals working in fraud detection machine learning, and how can they be addressed?

Professionals in Fraud Detection Machine Learning often face challenges such as dealing with highly imbalanced datasets, rapidly evolving fraud patterns, and the need for real-time detection. Managing data imbalance requires careful selection of evaluation metrics and specialized algorithms. Staying ahead of new fraud tactics involves continuous model retraining and close collaboration with domain experts. Additionally, integrating machine learning solutions with existing systems often requires cross-functional teamwork with IT, security, and compliance teams.

What is fraud detection using machine learning?

Fraud detection using machine learning involves leveraging algorithms and data analysis techniques to identify suspicious or fraudulent activities in various domains, such as banking, e-commerce, or insurance. These systems analyze large volumes of transaction data to detect patterns or anomalies that may indicate fraud. Machine learning models can adapt over time, improving their accuracy as they are exposed to more data. This approach helps organizations automate and enhance their ability to prevent, detect, and respond to fraudulent behavior efficiently.

What is the difference between Fraud Detection Machine Learning vs Fraud Analyst?

AspectFraud Detection Machine LearningFraud Analyst
CredentialsData science, machine learning certifications, programming skillsFinance, criminal justice degrees, analytical skills
Work EnvironmentData-driven, tech-focused, often in financial or e-commerce sectorsInvestigative, report-focused, in financial institutions or insurance companies
Employer & IndustryTech companies, banks, e-commerce platformsFinancial institutions, insurance firms, retail

Fraud Detection Machine Learning involves developing algorithms to identify fraudulent activities automatically, relying heavily on data analysis and programming. Fraud Analysts manually investigate suspicious cases and interpret data insights. While both roles aim to prevent fraud, Machine Learning specialists focus on building models, whereas Fraud Analysts focus on case investigation and decision-making.

What are the key skills and qualifications needed to thrive as a fraud detection machine learning specialist, and why are they important?

To thrive as a Fraud Detection Machine Learning Specialist, you need strong expertise in machine learning, statistical analysis, and programming languages like Python or R, typically supported by a degree in computer science, data science, or a related field. Familiarity with tools such as TensorFlow, Scikit-learn, SQL databases, and experience with big data platforms or cloud services is highly valuable. Critical thinking, attention to detail, and effective communication are crucial soft skills for identifying complex fraud patterns and collaborating with interdisciplinary teams. These competencies are vital for developing accurate models that protect organizations from financial losses and maintain trust with customers.

What job categories do people searching Fraud Detection Machine Learning jobs in Silver Spring, MD look for?

The top searched job categories for Fraud Detection Machine Learning jobs in Silver Spring, MD are:

What cities near Silver Spring, MD are hiring for Fraud Detection Machine Learning jobs?

Cities near Silver Spring, MD with the most Fraud Detection Machine Learning job openings:

Fraud Detection Machine Learning jobs near you
Infographic showing various Fraud Detection Machine Learning job openings in Silver Spring, MD as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $38,816 per year, or $18.7 per hour.

Senior AI/ML Lead

Elder Research

Arlington, VA • On-site

Full-time

Re-posted 26 days ago

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
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 careers@elderresearch.com and provide your name and contact information.

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