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Software Engineer Fraud Detection Jobs in Washington

Software Engineer 3

Annapolis Junction, MD ยท 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 ...

Data Engineer

Arlington, VA ยท On-site

$131K - $158K/yr

Dive into innovation in Digital Transformation, Cybersecurity, IT, Data Analytics and Software ... Your work will enable fraud detection, audit prioritization, refund review, and compliance risk ...

Data Engineer

Arlington, VA

$131K - $158K/yr

Dive into innovation in Digital Transformation, Cybersecurity, IT, Data Analytics and Software ... Your work will enable fraud detection, audit prioritization, refund review, and compliance risk ...

Data Engineer

Arlington, VA ยท On-site

$95 - $157/hr

Dive into innovation in Digital Transformation, Cybersecurity, IT, Data Analytics and Software ... Your work will enable fraud detection, audit prioritization, refund review, and compliance risk ...

Data Engineer

Arlington, VA ยท On-site

$62K - $141K/yr

... fraud detection to cancer research to national intelligence. As a Data Engineer at Booz Allen, you ... Experience writing software in programming languages, including Python * Knowledge of relational ...

Data Engineer

Arlington, VA ยท On-site

$62K - $141K/yr

... fraud detection to cancer research to national intelligence. As a Data Engineer at Booz Allen, you ... Experience writing software in programming languages, including Python * Knowledge of relational ...

Showing results 41-60

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 Washington?

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

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

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

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

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

Technical Analytics Manager / Lead Data Scientist (Fraud Analytics & Investigative Support)

Praescient Analytics

Fairfax, VA โ€ข On-site

$100 - $130/hr

Other

Retirement, PTO

Re-posted 11 days ago


Job description

Location: Remote (Occasional Travel May Be Required)

Clearance: Ability to obtain and maintain a Public Trust

Position Overview

Praescient Analytics is seeking a highly skilled Technical Analytics Manager / Lead Data Scientist to provide technical leadership for a federal fraud analytics and investigative support program. This individual will serve as the technical authority responsible for designing innovative analytic approaches, developing advanced fraud detection models, leading model validation and quality assurance activities, and ensuring the successful delivery of reliable, defensible, and repeatable analytic solutions supporting federal oversight organizations.

The ideal candidate is a handsโ€‘on technical leader who combines deep data science expertise with strong leadership skills. They will guide multidisciplinary technical teams through the full analytics lifecycle, from ideation and data exploration to model development, testing, deployment, and continuous improvement, while mentoring technical staff and collaborating closely with Government stakeholders, investigators, and program leadership.

Key Responsibilities
  • Lead the design, development, testing, validation, deployment, and continuous improvement of advanced fraud detection and investigative analytics solutions.
  • Develop innovative analytic approaches to identify fraud, waste, abuse, and mismanagement across large-scale federal benefit programs.
  • Design and implement analytic rules, machine learning models, artificial intelligence (AI) solutions, natural language processing (NLP), anomaly detection, entity resolution, graph analytics, link analysis, risk scoring, and other advanced analytic capabilities.
  • Lead technical teams responsible for model development, experimentation, quality assurance, documentation, and production deployment.
  • Perform handsโ€‘on development of analytic models using openโ€‘source programming languages, frameworks, and data science tools.
  • Conduct exploratory data analysis, feature engineering, data profiling, model evaluation, and performance optimization across complex datasets.
  • Establish and oversee rigorous quality control processes to ensure analytic outputs are accurate, reliable, repeatable, and fully documented prior to Government delivery.
  • Review technical work products, source code, analytic methodologies, and model outputs produced by contractor support teams.
  • Identify technical risks, recommend mitigation strategies, and ensure timely delivery of highโ€‘quality analytic products.
  • Collaborate with Project Managers, Data Engineers, Graph Data Scientists, Investigative Analysts, Forensic Accountants, and Government stakeholders throughout the project lifecycle.
  • Present analytic methodologies, technical findings, model performance, and recommendations to Government leadership, investigators, and oversight organizations.
  • Support Agile delivery through sprint planning, backlog refinement, technical demonstrations, and iterative model development.
Required Qualifications
  • Must have experience with Fraud Analysis
  • Five (5) or more years of handsโ€‘on experience developing analytic rules and models for fraud detection use cases using leadingโ€‘edge analytic tools and best practices.
  • Five (5) or more years of experience designing analytic approaches, managing model development and testing efforts, and conducting thorough quality control.
  • Demonstrated experience ideating innovative analytic use cases to detect and prevent fraud, waste, abuse, and mismanagement.
  • Five (5) or more years of experience tracking project progress, identifying technical risks, and delivering highโ€‘quality analytic solutions on schedule.
  • Five (5) or more years of experience reviewing contractorโ€‘developed analytic models, code, methodologies, and work products prior to final delivery.
  • Five (5) or more years of handsโ€‘on experience developing analytic rules and models using openโ€‘source programming languages and frameworks.
  • Strong written, verbal, presentation, and technical communication skills.
  • Demonstrated ability to lead technical teams while remaining actively engaged in handsโ€‘on analytics development.
Preferred Qualifications

Preference will be given to candidates with demonstrated experience in one or more of the following areas:

  • Developing fraud detection, fraud prevention, and program integrity analytics supporting pandemic relief, emergency assistance, grants, loans, healthcare, unemployment insurance, disaster relief, financial assistance, or other highโ€‘volume federal benefit programs.
  • Designing, developing, validating, deploying, and maintaining advanced analytic models utilizing machine learning, artificial intelligence (AI), natural language processing (NLP), anomaly detection, entity resolution, graph analytics, link analysis, knowledge graphs, risk scoring, or robotic process automation (RPA).
  • Applying openโ€‘source programming languages and frameworks such as Python, SQL, Spark, Pandas, Scikitโ€‘learn, TensorFlow, PyTorch, or comparable data science technologies.
  • Developing analytics within cloudโ€‘native environments utilizing Azure Databricks, Microsoft SQL Server, Microsoft Fabric, Azure Data Lake, Power BI, Neo4j, Git repositories, Lakehouse architectures, or enterprise data catalogs.
  • Working with largeโ€‘scale public, nonโ€‘public, commercial, financial, and law enforcement datasets to identify organized fraud rings, synthetic identities, duplicate entities, eligibility issues, and emerging fraud schemes.
  • Conducting exploratory data analysis, data profiling, feature engineering, model validation, performance testing, and quality assurance throughout the analytics lifecycle.
  • Supporting Offices of Inspector General (OIGs), law enforcement organizations, oversight agencies, or program integrity initiatives through advanced analytic solutions.
  • Developing reproducible analytic workflows that emphasize governance, documentation, transparency, explainability, and enterprise data management best practices.
  • Leading technical reviews, mentoring data scientists, and establishing quality standards for analytic products delivered to Government customers.
What We're Looking For

We're looking for a technical leader who enjoys solving complex fraud detection challenges while remaining actively involved in handsโ€‘on analytics development. The ideal candidate is equally comfortable writing code, designing machine learning models, reviewing technical work products, mentoring fellow data scientists, and briefing analytic findings to senior Government stakeholders. They combine innovative thinking with disciplined engineering practices to ensure every analytic solution is technically sound, operationally effective, and capable of supporting realโ€‘world investigative and oversight missions.

What you can expect from us:
  • Real opportunity for career growth in an environment where your achievements will be celebrated
  • Constant collaboration with numerous teams to ensure client success
  • A team that respects and embraces your ideas and expertise
  • Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain
  • A workplace dedicated to supporting and bettering public safety and government agencies
Benefits:
  • Competitive salary based on qualifications and experience
  • Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)
  • 401(k) with company match
  • Travel & performance incentives
  • 3 weeks paid time off (plus Federal Holidays)
  • $5K annual training allowance
  • $500 book allowance
  • Tuition reimbursement program

Praescient Analytics is an Equal Employment Opportunity employer. Employment decisions are based on merit, qualifications, experience, performance, business needs, and applicable contract requirements. Praescient does not unlawfully discriminate or provide disparate treatment based on race, ethnicity, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other status protected by applicable law.
Praescient Analytics acknowledges the applicable clause and provision updates implementing Executive Order 14398, Addressing DEI Discrimination by Federal Contractors, and the related FAR/RFO updates, including FAR 52.222-90 where applicable. Praescient does not engage in racially discriminatory DEI activities, including disparate treatment based on race or ethnicity in recruitment, hiring, promotion, contracting, program participation, training, mentoring, leadership development, or allocation of company resources. Praescientโ€™s employment and contracting decisions are made based on merit, qualifications, experience, performance, business needs, and applicable contract requirements.

Applicants selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information. US Citizenship Required Interested Candidates: Please forward your resume to recruiting@praescientanalytics.com and please visit our website to apply online at www.praescientanalytics.applicantstack.com/x/openings.

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