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Software Engineer Fraud Detection Jobs in Maryland

GDIT

Software Engineer 3

Annapolis Junction, MD · On-site

$175K - $238K/yr

... detection Experience with Git Source Control System Position Desired Skills Familiar with HPC Job ... We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding ...

GDIT

Software Engineer

Annapolis Junction, MD · Hybrid

$187K - $230K/yr

Software Engineering Job Qualifications: Skills: AWS Tools, Docker (Software), GitLab, Kubernetes ... We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding ...

GDIT

Software Engineer

Annapolis Junction, MD · On-site

$175K - $238K/yr

Yes SOFTWARE ENGINEER Praxis Engineering, A GDIT company, creates exciting and novel mission ... We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding ...

GDIT

Software Engineer

Annapolis Junction, MD · On-site

$114K - $155K/yr

None Job Family: Software Engineering Job Qualifications: Skills: Dev-C++, Device Driver ... We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding ...

Booz Allen Hamilton

Software Engineer

Lexington Park, MD · On-site

$69K - $158K/yr

Software Engineer The Opportunity: As a full stack developer, you can resolve a problem with a ... We reserve the right to take your picture to verify your identity and prevent fraud. Candidate AI ...

Booz Allen Hamilton

Software Engineer

Lexington Park, MD · On-site

$69K - $158K/yr

R0243159 Software Engineer The Opportunity: As a full stack developer, you can resolve a problem ... We reserve the right to take your picture to verify your identity and prevent fraud. Candidate AI ...

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Software Engineer Fraud Detection information

What does a software engineer fraud detection do?

A Software Engineer in Fraud Detection designs and develops systems to identify and prevent fraudulent activities within digital platforms, such as banking or e-commerce environments. They build algorithms to analyze user behavior, detect anomalies, and flag suspicious transactions in real time. Their work often involves machine learning, big data analysis, and close collaboration with data scientists and security teams to continuously improve fraud detection accuracy. These engineers play a key role in protecting businesses and customers from financial loss and cybercrime.

How does a software engineer fraud detection typically collaborate with data scientists and analysts to identify fraudulent activity?

Software Engineers in Fraud Detection work closely with data scientists and analysts to build, refine, and deploy systems that detect and prevent fraud. While data scientists may develop models and identify patterns from large datasets, engineers are responsible for integrating these models into scalable, real-time systems within the company's technology stack. Regular communication and joint problem-solving are essential, as engineers must understand the logic behind models and analysts' findings to ensure accurate implementation and continuous improvement. This collaborative environment helps create robust fraud detection mechanisms that adapt to evolving threats.

What are the key skills and qualifications needed to thrive as a software engineer fraud detection, and why are they important?

To thrive as a Software Engineer in Fraud Detection, strong programming skills (such as Python, Java, or Scala), a solid understanding of algorithms, data structures, and experience with machine learning or statistical analysis are generally required, often supported by a degree in computer science or a related field. Familiarity with big data platforms (like Hadoop or Spark), real-time analytics systems, and fraud detection tools or frameworks is typically expected. Analytical thinking, problem-solving abilities, and effective communication are key soft skills that differentiate top performers in this field. These skills are crucial for developing robust systems that can quickly identify and prevent fraudulent activities, protecting both users and organizations.

What is the difference between Software Engineer Fraud Detection vs Data Scientist Fraud Detection?

AspectSoftware Engineer Fraud DetectionData Scientist Fraud Detection
Required CredentialsBachelor's in CS or related field, programming skillsBachelor's or higher in CS, Statistics, or Data Science
Work EnvironmentDevelops fraud detection systems, writes code, implements algorithmsAnalyzes data, builds models, interprets results
Employer & Industry UsageFinancial institutions, fintech, e-commerceFinancial services, tech companies, insurance
Common Search & ComparisonFocuses on software development for fraud detectionFocuses on data analysis and modeling for fraud detection

While both roles work in fraud detection, Software Engineer Fraud Detection primarily develops and maintains detection systems through coding, whereas Data Scientist Fraud Detection analyzes data and builds models to identify fraudulent activity. Both roles often collaborate but differ in their core focus and skill sets.

What are popular job titles related to Software Engineer Fraud Detection jobs in Maryland?

For Software Engineer Fraud Detection jobs in Maryland, the most frequently searched job titles are:

What job categories do people searching Software Engineer Fraud Detection jobs in Maryland look for?

The top searched job categories for Software Engineer Fraud Detection jobs in Maryland are:

What cities in Maryland are hiring for Software Engineer Fraud Detection jobs?

Cities in Maryland with the most Software Engineer Fraud Detection job openings:

Software Engineer Fraud Detection jobs near you
Infographic showing various Software Engineer Fraud Detection job openings in Maryland as of August 2026, with employment types broken down into 92% Full Time, 6% Part Time, and 2% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Senior Software Engineer - Security

T Rowe Price

Owings Mills, MD • Hybrid

$116K - $154K/yr

Full-time

Re-posted 28 days ago

Key responsibilities

  • Design, develop, and modify fraud detection software and related systems.

  • Review and interpret system requirements, code, test, debug, and implement software solutions.

  • Lead projects or work streams, review code, and provide feedback to team members.

T. Rowe Price rating

9.1

Company rating: 9.1 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

Job description

Role Summary

We are seeking a full stack Senior Software Engineer - Security and Data Engineering experience. In this role you will be responsible for the design, development, and operations of fraud detection software in a highly collaborative environment. You will use a combination of data engineering, software engineering, and Python based frameworks, and tooling, to harness data sources for the purpose of identifying fraud and preventing loss for our external customers.

In this role you will also design, develop, modify, adapt and implement short- and long-term solutions to information technology needs through new and existing applications, systems, databases and applications infrastructure. You will review and interpret system requirements and business processes as well as code, test, debug and implement software solutions. You will also:

  • Lead projects or work streams.
  • Be accountable for your work and sometimes others, provide process and standards advice in your area of specialization.
  • Work independently.
  • Serve as a resource for colleagues with less experience.

Responsibilities

  • Performing as a domain expert in one or more parts of the software lifecycle (e.g., coding, testing, deployment). Leads significant pieces of development within the development lifecycle.
  • Contributing to the development of standard methodologies within your group.
  • Leading code reviews and actively participates in providing feedback on others' designs/code.
  • Being accountable for technical debt in your own software.
  • Leading a small project team, as required.
  • Taking control of complex problems and step through them in a rational way.
  • Making tactical vs. strategic trade-offs.
  • Being flexible in your thinking; able to evolve a solution when additional information or ideas are presented.
  • Mentoring junior members of the team.
  • Identifying when junior engineers need help and providing it in a positive way that promotes confidence.
  • Actively helping team members/make suggestions to improve practices.

Business Knowledge:

  • Able to work directly with business partners.
  • Decisions show a focus on current and future business priorities, together with fiscal responsibility.
  • Can articulate business needs and translate them into technology solutions.

Qualifications

Required:

  • Bachelor's Degree (or the equivalent combination of education and relevant experience) and 5+ years of progressive software engineering experience
  • In-depth knowledge and expertisein your job discipline and working knowledge of related disciplines.
  • Stays up to date with new technologies.
  • Shows dedication to quality by implementing suitable software using unit/integration and acceptance testing at the time of feature development.
  • Debugs large components with limited assistanceand assistsother engineerswith debugging.
  • Designs and develops practical APIs and abstractions.
  • Experience with Data Engineering tools and technologies (Deltalake, Lakehouse, Iceberg, Snowflake, and Apache Spark).
  • Experience with Amazon Web Services (AWS).
  • Experience with React and Django framework.
  • Experience with Python ML packages.
  • Programs proficiently in Python and JavaScript.
  • Shows a commitment to quality by implementing suitable software using unit/integration and acceptance testing at the time of feature development.
  • Develops data models or schemas from scratch and knows of key concepts such as ACID, Normalization, and Transactions.
  • Leads code reviews, actively participatesin providing feedback on others' designs/code, helps others solve technical problems.
  • Able to provide a clear and concise explanation of technical concepts, designs, or implementations.
  • Proficient in writing complex queries to pull data from various tools such as Splunk, DbVisualizer, Oracle or DB2.
  • Proficient in Splunk, including lookup tables, reports, creating alerts, and creating Splunk dashboards.

Preferred:

  • A demonstrable knowledge of fraud risk factors and analysis, suchas IP address, cookies, user-agents, banks, redemptions, loan, and withdrawals.
  • A general knowledge of aggregators, rules, and rules engines.
  • Good knowledge of authentication, MFA, security questions, everify, and Quovosystems.
  • Experience with JupyterNotebook and Pandas.

FINRA Requirements

FINRA licenses are not required and will not be supported for this role.

Work Flexibility

This role is eligible for hybrid work, with up to three days per week from home.

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