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ArdentMC

Graph Data Scientist

Reposted 4 Days Ago
Remote
Hiring Remotely in USA
Mid level
Remote
Hiring Remotely in USA
Mid level
Develop and operationalize graph-based analytics for fraud detection and investigative analysis. Build graph models, apply graph algorithms and ML to detect anomalies, support entity resolution, create visualizations and dashboards, and collaborate with investigators and stakeholders to deploy and maintain production solutions.
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At Ardent, we hire people who want more than a job — they want to serve a mission that matters. Our teams support the federal government’s most critical national security and defense priorities, helping protect the nation, strengthen resilience, and advance the technologies and capabilities that keep America secure. For veterans, cleared professionals, and purpose-driven innovators, Ardent is a place to continue serving alongside a team that understands the importance of the mission and the people behind it.

We also know top talent has choices, which is why we back our mission with benefits and flexibility that stand out: competitive pay, comprehensive health coverage, flexible PTO, federal holidays off, tuition reimbursement, professional development support, wellness stipends, and a culture that values and rewards hard work, dedication, and adaptability. If you want to build something meaningful, while enjoying the kind of flexibility and support that you need to do your best work — Ardent is where your next mission begins.

Ardent is seeking a Graph Data Scientist to join our team.  

This is a remote position.

Position Description:

Ardent is seeking a Graph Data Scientist to develop graph-based analytics solutions supporting fraud prevention, investigative analysis, and program integrity initiatives within a federal environment.

This role will focus on using graph databases, network analysis, statistical methods, and machine learning techniques to identify relationships, hidden connections, suspicious activity, and emerging fraud patterns across large and complex datasets. The Graph Data Scientist will work closely with data scientists, investigators, analysts, data engineers, and government stakeholders to design, implement, and operationalize graph analytics capabilities.

Responsibilities and Duties:

  • Design, develop, and implement graph-based analytics solutions supporting fraud detection and investigative analysis.
  • Use graph databases and network analysis techniques to identify hidden relationships, patterns, and connections across entities.
  • Develop graph models representing individuals, organizations, transactions, accounts, programs, and other relevant entities.
  • Apply graph algorithms involving centrality, community detection, link analysis, path analysis, clustering, and anomaly detection.
  • Integrate graph analytics with machine learning, statistical analysis, and other advanced analytic methods.
  • Analyze structured, semi-structured, and unstructured data from public, non-public, and commercial sources.
  • Support entity resolution, identity matching, relationship mapping, and risk-scoring activities.
  • Develop and refine fraud-detection models, rules, and investigative use cases.
  • Collaborate with investigators and analysts to translate operational and investigative needs into graph analytics solutions.
  • Build visualizations, link charts, dashboards, and other work products that clearly communicate complex relationships.
  • Support the development, testing, validation, and deployment of graph analytics models and applications.
  • Evaluate model performance and recommend adjustments to improve accuracy, scalability, and usefulness.
  • Document methodologies, data sources, assumptions, model designs, findings, and limitations.
  • Participate in technical reviews, quality-control activities, and project demonstrations.
  • Present analytical findings and recommendations to technical and non-technical stakeholders.
  • Support the maintenance and improvement of deployed graph analytics solutions.

Requirements: 

  • Minimum of 3 years of hands-on experience using Neo4j or a similar graph database.
  • Proficiency with Cypher or a comparable graph query language.
  • Minimum of 3 years of hands-on experience applying graph methods to fraud detection, investigative analytics, risk analysis, or knowledge graph initiatives.
  • Strong understanding of network topology, centrality measures, community detection, path analysis, clustering, and relationship analysis.
  • Minimum of 3 years of experience applying statistical and machine learning techniques to graph-structured data.
  • Experience working with graph algorithms, anomaly detection, classification, or predictive modeling.
  • Experience designing, implementing, and optimizing graph data pipelines, data models, and graph schemas.
  • Experience working with large, complex, and high-volume datasets.
  • Strong Python skills using standard machine learning, data science, and graph analytics libraries.
  • Experience with data preparation, feature engineering, model validation, and performance evaluation.
  • Experience communicating complex analytical findings through visualizations, reports, and presentations.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to collaborate with technical teams, investigators, analysts, and government stakeholders.
  • Ability to successfully complete and maintain the required government background investigation.

Preferred Qualifications: 

  • Experience supporting federal fraud prevention, investigative, oversight, or program-integrity initiatives.
  • Experience working with Offices of Inspectors General, law enforcement organizations, or federal benefit programs.
  • Experience developing graph analytics solutions involving fraud rings, identity fraud, financial networks, or suspicious relationship patterns.
  • Experience with Neo4j Graph Data Science, NetworkX, PyTorch Geometric, DGL, or similar graph analytics libraries.
  • Experience with knowledge graphs, entity resolution, link prediction, or graph embeddings.
  • Experience integrating graph databases with cloud platforms, data lakes, or enterprise analytics environments.
  • Experience with Azure Databricks, Microsoft SQL Server, Power BI, or comparable technologies.
  • Experience deploying graph analytics solutions into production environments.
  • Bachelor’s or advanced degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.

Due to the nature of the work we support, all candidates in consideration for this role must be willing to undergo the government issued background investigation process. We highly encourage all Veterans and those with disabilities to apply.

Ardent is an equal opportunity employer. We will not discriminate in employment, recruitment, advertisements for employment, compensation, termination, upgrading, promotions, and other conditions of employment against any employee or job applicant on the bases of race, color, gender, national origin, age, religion, creed, disability, veteran's status, sexual orientation, gender identity, gender expression, or any other basis protected by state, local, or federal law.

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