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Graph Strategy Jobs in Manassas, VA (NOW HIRING)

BTI360 Inc

NLP Engineer with Security Clearance

Herndon, VA · On-site

$117K - $141K/yr

... strategy, and help our customers navigate high‑impact mission challenges. What you will do in this role: As an NLP Engineer at BTI360, you will: • Lead end-to-end knowledge graph and ...

BTI360

NLP Engineer - Clearance Required

Herndon, VA · On-site

... and strategic initiatives. • Mentor junior data scientists by providing technical guidance, defining project direction, and sharing best practices in graph-oriented data modeling, extraction ...

Leidos

Senior Data Scientist

Glen Echo, MD · On-site

$107K - $195K/yr

  • Medical

  • Retirement

  • PTO

Prototype ingestion pipelines that support scalable graph analytics. * Support data engineering in implementations of data schemas, indexing strategies, and partitioning approaches to maximize query ...

Leidos

Senior Data Scientist

Bethesda, MD

Prototype ingestion pipelines that support scalable graph analytics. * Support data engineering in implementations of data schemas, indexing strategies, and partitioning approaches to maximize query ...

Leidos

Senior Data Scientist

Bethesda, MD · On-site

Prototype ingestion pipelines that support scalable graph analytics. * Support data engineering in implementations of data schemas, indexing strategies, and partitioning approaches to maximize query ...

Leidos

Senior Data Scientist

Rockville, MD · On-site

$107K - $195K/yr

  • Medical

  • Retirement

  • PTO

Prototype ingestion pipelines that support scalable graph analytics. * Support data engineering in implementations of data schemas, indexing strategies, and partitioning approaches to maximize query ...

Leidos

Senior Data Scientist

Bethesda, MD · On-site

$107K - $195K/yr

  • Medical

  • Retirement

  • PTO

Prototype ingestion pipelines that support scalable graph analytics. * Support data engineering in implementations of data schemas, indexing strategies, and partitioning approaches to maximize query ...

Leidos

Senior Data Scientist

Chevy Chase, MD · On-site

$107K - $195K/yr

  • Medical

  • Retirement

  • PTO

Prototype ingestion pipelines that support scalable graph analytics. * Support data engineering in implementations of data schemas, indexing strategies, and partitioning approaches to maximize query ...

Leidos

Senior Data Scientist

Bethesda, MD · On-site

$107K - $195K/yr

  • Medical

  • Retirement

  • PTO

Prototype ingestion pipelines that support scalable graph analytics. * Support data engineering in implementations of data schemas, indexing strategies, and partitioning approaches to maximize query ...

Leidos

Senior Data Scientist

Arlington, VA · On-site

$107K - $195K/yr

  • Medical

  • Retirement

  • PTO

Prototype ingestion pipelines that support scalable graph analytics. * Support data engineering in implementations of data schemas, indexing strategies, and partitioning approaches to maximize query ...

Via Logic LLC

Senior Data Scientist

Bethesda, MD · On-site

$107.90 - $195.05/hr

  • Medical

  • Retirement

  • PTO

Prototype ingestion pipelines that support scalable graph analytics. * Support data engineering in implementations of data schemas, indexing strategies, and partitioning approaches to maximize query ...

VTG

Software Engineer

Chantilly, VA · On-site

Develop graph traversal capabilities using Apache TinkerPop, Gremlin, JanusGraph, or similar ... Design partition and sort key strategies to ensure consistent system performance. * Develop ...

VTG

Software Engineer

Chantilly, VA · Remote

Develop graph traversal capabilities using Apache TinkerPop, Gremlin, JanusGraph, or similar ... Design partition and sort key strategies to ensure consistent system performance. * Develop ...

Leidos

Senior Data Engineer

Chevy Chase, MD · On-site

$131K - $237K/yr

  • Medical

  • Retirement

  • PTO

Develop scalable ingestion pipelines that support scalable graph analytics. * Design data schemas, indexing strategies, and partitioning approaches to maximize query performance, scalability, and ...

Leidos

Senior Data Engineer

Bethesda, MD · On-site

$131K - $237K/yr

  • Medical

  • Retirement

  • PTO

Develop scalable ingestion pipelines that support scalable graph analytics. * Design data schemas, indexing strategies, and partitioning approaches to maximize query performance, scalability, and ...

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Showing results 21-40

All JobsGraph Strategy JobsGraph Strategy Jobs in Manassas, VA

Graph Strategy information

See Manassas, VA salary details

$55.5K

$124.6K

$217.4K

How much do graph strategy jobs pay per year?

As of Aug 15, 2026, the average yearly pay for graph strategy in Manassas, VA is $124,630.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $157,500.00 per year, depending on experience, location, and employer.

What is a graph strategy?

A Graph Strategy job typically involves working with graph databases or technologies to analyze and model complex relationships among data points. Professionals in this role develop strategies for leveraging graph structures to solve business problems, such as optimizing network connections, detecting fraud, or improving recommendation systems. They often collaborate with data scientists, engineers, and business stakeholders to design, implement, and maintain graph-based solutions. This job requires strong analytical skills, a deep understanding of graph theory, and experience with graph database technologies like Neo4j. The goal is to extract valuable insights from interconnected data to drive strategic decisions.

How does a graph strategy professional typically collaborate with data engineers and business analysts within an organization?

A Graph Strategy professional often acts as a bridge between technical teams (like data engineers) and business stakeholders (such as business analysts). They work closely with data engineers to design and optimize graph databases or knowledge graphs, ensuring that the underlying data structures support business needs. Simultaneously, they partner with business analysts to identify use cases, interpret data relationships, and translate business questions into graph queries or visualizations. This role requires both technical understanding and strong communication skills to align data assets with strategic business objectives.

What is the difference between Graph Strategy vs Data Analyst?

AspectGraph StrategyData Analyst
Required CredentialsOften requires knowledge of data visualization, analytics tools, and strategic planningTypically requires a degree in statistics, mathematics, or related fields; proficiency in Excel, SQL, and data analysis software
Work EnvironmentStrategic planning sessions, data visualization projects, cross-department collaborationData collection, cleaning, analysis, reporting, and presenting insights
Employer & Industry UsageUsed in marketing, finance, and tech companies for strategic decision-makingCommon in business, finance, healthcare, and tech sectors for data-driven insights

While both roles involve working with data, Graph Strategy focuses on creating visual data representations to inform strategic decisions, whereas Data Analysts primarily analyze data sets to generate actionable insights. Understanding these differences helps organizations assign the right roles for their data needs.

What are the key skills and qualifications needed to thrive as a graph strategy professional, and why are they important?

To thrive as a Graph Strategy professional, you need a strong background in mathematics, data analysis, and graph theory, often supported by a degree in computer science, mathematics, or a related field. Familiarity with graph databases (e.g., Neo4j), data visualization tools, and relevant programming languages like Python or Cypher is typically required. Strategic thinking, problem-solving, and effective communication are essential soft skills for translating complex data insights into actionable business strategies. These skills enable professionals to leverage graph structures for advanced analytics, driving informed decisions and competitive advantage.

What job categories do people searching Graph Strategy jobs in Manassas, VA look for?

The top searched job categories for Graph Strategy jobs in Manassas, VA are:

What cities near Manassas, VA are hiring for Graph Strategy jobs?

Cities near Manassas, VA with the most Graph Strategy job openings:

Graph Strategy jobs near you
Infographic showing various Graph Strategy job openings in Manassas, VA as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $124,630 per year, or $59.9 per hour.

Graph Data Scientist (Fraud Analytics & Investigative Support)

Praescient Analytics

Fairfax, VA • On-site, Remote

Full-time

Retirement, PTO

Re-posted 20 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 an experienced Graph Data Scientist to develop advanced graph analytics that uncover hidden relationships, organized fraud networks, synthetic identities, and other complex patterns supporting federal fraud detection and investigative missions. This individual will leverage graph databases, graph algorithms, and machine learning techniques to transform large, interconnected datasets into actionable intelligence for investigators, analysts, and oversight organizations.
The ideal candidate is a hands-on technical specialist with deep expertise in graph theory, Neo4j, and graph-based machine learning. They thrive on solving complex network problems, building scalable graph data models, and discovering non-obvious relationships that traditional analytics cannot detect.
Key Responsibilities
  • Design, develop, and maintain graph-based analytic solutions supporting fraud detection, investigative analysis, and program integrity initiatives.
  • Build and optimize graph databases, graph schemas, and knowledge graphs using Neo4j or comparable graph database technologies.
  • Develop graph queries using Cypher or similar graph query languages to identify hidden relationships, fraud rings, suspicious networks, synthetic identities, and other complex entity relationships.
  • Apply graph algorithms, statistical analysis, and machine learning techniques to identify emerging fraud patterns and anomalous network behavior.
  • Design graph data models and scalable graph data pipelines that integrate structured and unstructured data from multiple public, non-public, commercial, and law enforcement data sources.
  • Perform network analysis utilizing centrality measures, community detection, shortest path algorithms, clustering, and graph-based anomaly detection techniques.
  • Collaborate with Data Engineers, Data Scientists, Investigative Analysts, and Technical Analytics Managers to integrate graph analytics into broader fraud detection models.
  • Validate graph analytic outputs, document methodologies, and ensure graph models are accurate, explainable, and reproducible.
  • Develop visualizations and relationship analyses that support investigative lead generation, case development, and executive briefings.
  • Support continuous improvement of graph analytics capabilities through experimentation with emerging graph technologies, graph machine learning techniques, and knowledge graph methodologies.

Required Qualifications
  • Must have experience with Fraud Analysis
  • Three (3) or more years of hands-on experience developing graph analytics using Neo4j or a comparable graph database platform.
  • Demonstrated fluency in Cypher or a comparable graph query language.
  • Strong understanding of graph theory and network analytics, including network topology, centrality measures, community detection, shortest path algorithms, graph clustering, and graph traversal techniques.
  • Three (3) or more years of hands-on experience applying statistical analysis, machine learning, clustering, classifiers, and anomaly detection techniques to graph-structured data.
  • Three (3) or more years of experience applying graph methods to fraud detection, relationship discovery, link analysis, and knowledge graph development.
  • Experience designing graph data models, graph schemas, and graph data pipelines supporting large-scale, high-complexity datasets.
  • Strong Python programming skills utilizing standard machine learning libraries and data science frameworks.
  • Excellent written and verbal communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences.

Preferred Qualifications
Preference will be given to candidates with demonstrated experience in one or more of the following areas:
  • Applying graph analytics to fraud detection, fraud prevention, financial crime investigations, program integrity, anti-money laundering (AML), or other complex investigative environments.
  • Developing graph solutions supporting federal benefit programs, emergency relief initiatives, financial assistance programs, healthcare fraud, unemployment insurance fraud, grants management, or other high-volume public-sector programs.
  • Building knowledge graphs that integrate multiple public, non-public, commercial, financial, and law enforcement data sources into unified entity networks.
  • Detecting organized fraud rings, synthetic identities, shell companies, nominee entities, shared addresses, common bank accounts, related businesses, and other non-obvious relationships through graph analytics.
  • Designing and optimizing graph data pipelines, graph schemas, graph indexing strategies, and graph performance for enterprise-scale analytics environments.
  • Applying graph data science algorithms including PageRank, Louvain community detection, connected components, similarity algorithms, node embeddings, graph embeddings, link prediction, and graph-based anomaly detection.
  • Developing graph analytics within cloud-native environments utilizing Neo4j, Azure Databricks, Microsoft SQL Server, Azure Data Lake, Microsoft Fabric, Power BI, Git repositories, or Lakehouse architectures.
  • Leveraging Python libraries such as NetworkX, Neo4j Graph Data Science (GDS), Pandas, Scikit-learn, PyTorch Geometric, or comparable graph analytics and machine learning frameworks.
  • Supporting Offices of Inspector General (OIGs), law enforcement organizations, intelligence organizations, financial crime investigations, or other government oversight missions.
  • Developing interactive graph visualizations, relationship maps, and investigative link analysis products that accelerate lead generation, case development, and investigative decision-making.

What We're Looking For
We're looking for someone who sees relationships where others see disconnected data. The ideal candidate enjoys solving complex network problems, discovering hidden fraud patterns, and transforming interconnected datasets into actionable investigative intelligence. They combine strong graph theory fundamentals with practical engineering skills to build scalable graph analytics that help investigators identify organized fraud networks, prioritize investigative leads, and uncover relationships that would otherwise remain hidden.
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. Praescient'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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