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Fraud Detection Machine Learning Jobs in Silver Spring, MD

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

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 ...

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 ...

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 ...

Senior Cybersecurity Program Manager

Washington, DC ยท On-site

$131K - $131K/yr

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

Machine Learning Engineer

Washington, DC ยท On-site +1

$130K - $200K/yr

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 ...

Machine Learning Engineer

Washington, DC ยท On-site +1

$130K - $200K/yr

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 ...

Machine Learning Engineer

Washington, DC ยท On-site

$130K - $200K/yr

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 ...

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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 Jun 14, 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 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 Analytics Subject Matter Expert

Fraud Analytics Subject Matter Expert

Elder Research

Arlington, VA โ€ข Hybrid

Other

Posted 25 days ago


Job description

Fraud Analytics Subject Matter Expert


General Information

Requisition # 684

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 Fraud Analytics Subject Matter Expert 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 Fraud Analytics Subject Matter Expert (SME) to provide deep domain expertise supporting fraud detection and identity theft analytics initiatives. This role guides analytical development, validates analytical outputs, and ensures models and analytical results accurately reflect real-world fraud behaviors and operational realities.

The ideal candidate brings extensive experience analyzing fraud patterns and supporting operational fraud detection programs within government or financial institutions.

Responsibilities include but are not limited to:

  • Provide domain expertise in fraud detection, identity theft, and financial crime analytics.
  • Guide analytical teams in identifying fraud schemes, patterns, and emerging threats.
  • Validate analytical outputs through return-level or case-level analysis.
  • Assist in interpreting model results and analytical findings.
  • Support collaborative reviews, stakeholder briefings, and operational discussions.
  • Help refine analytical approaches based on evolving fraud behaviors and operational insights.
  • Contribute to documentation of fraud patterns, analytical logic, and investigative insights.

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
  • 5+ years of experience in fraud analytics, identity theft analysis, financial crime analytics, or compliance program support.
  • Deep understanding of fraud schemes, filing behaviors, and investigative treatment processes
  • Experience validating analytical outputs through case-level or transaction-level review.
  • Demonstrated experience supporting fraud analytics within a federal agency, financial institution, or similarly regulated environment.
  • Strong knowledge of fraud detection, anomaly detection, risk scoring, and network analysis techniques.
  • Experience working with large financial or tax datasets in enterprise analytical environments.
  • Familiarity with analytical tools including SQL, Python, and enterprise analytics platforms.

Preferred Qualifications:

  • Advanced degree (MS) in analytics, computer science, data science, mathematics, statistics, engineering, management information systems, decision science, or related fields
  • Working knowledge of federal tax forms, filing processes, information returns, refund issuance workflows, and identity theft treatments.
  • Ability to translate analytical findings into insights useful for operational fraud programs.

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.