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Fraud Detection Machine Learning Jobs in Silver Spring, MD

Varsity Tutors

Machine Learning Tutor

Rockville, MD · Remote

$18 - $40/hr

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

Varsity Tutors

Machine Learning Tutor

Laurel, MD · Remote

$18 - $40/hr

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

Varsity Tutors

Machine Learning Tutor

College Park, MD · Remote

$18 - $40/hr

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

Varsity Tutors

Machine Learning Tutor

Washington, DC · Remote

$18 - $40/hr

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

Varsity Tutors

Machine Learning Tutor

Alexandria, VA · Remote

$18 - $40/hr

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

Varsity Tutors

Machine Learning Tutor

Baltimore, MD · Remote

$18 - $40/hr

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

Varsity Tutors

Machine Learning Tutor

Bowie, MD · Remote

$18 - $40/hr

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

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Fraud Detection Machine Learning information

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

As of Sep 3, 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 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 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 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 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 popular job titles related to Fraud Detection Machine Learning jobs in Silver Spring, MD?

For Fraud Detection Machine Learning jobs in Silver Spring, MD, the most frequently searched job titles 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.

Technical Analytics Manager/Lead Data Scientist

Magnus Management Group LLC

Washington, DC • Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 21 days ago

Job description

Benefits:
  • 401(k)
  • Dental insurance
  • Health insurance
  • Paid time off
  • Vision insurance

We are seeking Technical Analytics Manager/Lead Data Scientist to lead the design, development, testing, validation, and deployment of advanced analytics, machine learning models, and AI-enabled fraud detection capabilities supporting federal oversight and investigative activities.
The successful candidate will provide technical leadership across multiple analytics projects while ensuring high-quality deliverables, mentoring technical teams, and collaborating with government stakeholders to detect fraud, waste, abuse, and mismanagement across large federal benefit programs.
Responsibilities:
  • Should have five (5) or more years of hands-on experience developing analytic rules and models for fraud detection use cases using leading edge analytic tools and best practices. 
  • Should have five (5) or more years of hands-on experience designing analytic approaches, managing model development and testing efforts and conducting thorough quality control. 
  • Must have experience ideating use cases using innovative approaches to detect and prevent fraud, waste, abuse and mismanagement. 
  • Should have five (5) or more years of tracking project progress and identifying and mitigating risks and issues associated with delivering projects on time and at a high level of quality. 
  • Should have five (5) or more years of conducting thorough review and quality control on contractor support teams’ work products before analytic models and insights are finalized 
  • Must have five (5) or more years of hands-on experience coding rules and models using open-source programming techniques and tools. 
  • Must have strong oral and written skills. 
Minimum Qualifications
  • Minimum 5 years developing fraud detection analytics. 
  • Minimum 5 years designing analytic approaches and managing model development. 
  • Minimum 5 years coding in Python or other open-source programming languages. 
  • Experience with machine learning, anomaly detection, predictive analytics, and AI. 
  • Experience leading technical teams. 
  • Excellent verbal and written communication skills. 
Preferred Qualifications
  • Experience supporting federal oversight agencies. 
  • Experience with Databricks, SQL Server, Azure. 
  • Experience supporting fraud detection for federal benefit programs. 
  • Experience with graph analytics and Neo4j. 

This is a remote position.