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Graph Data Scientist

3 weeks, 1 day ago
United States
Full-time
Mid Level
Data Scientist
Data Science and Analytics
Feature Engineering Machine Learning Neo4j Power BI Python SQL Server
Apply Now
Ardent MC

Ardent MC

ArdentMC provides digital transformation, data science, and location intelligence solutions for security and defense missions, offering innovative IT services and expertise in situational awareness and geographic visualization.

Construction & Engineering
51-250
Founded 2006
View All Jobs 6

Description

  • Design, develop, and implement graph-based analytics solutions for fraud detection and investigative analysis.
  • Use graph databases and network analysis to identify hidden relationships, patterns, and connections across entities.
  • Develop graph models for individuals, organizations, transactions, accounts, programs, and related entities.
  • Apply graph algorithms such as 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, analysts, engineers, and government stakeholders to translate needs into analytics solutions.
  • Build visualizations, link charts, dashboards, and other outputs that communicate complex relationships clearly.
  • Support testing, validation, deployment, maintenance, and improvement of graph analytics models and applications.
  • Evaluate model performance and recommend changes to improve accuracy, scalability, and usefulness.
  • Document methodologies, data sources, assumptions, model designs, findings, and limitations.
  • Present analytical findings and recommendations to technical and non-technical stakeholders.

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

Benefits

  • Competitive pay.
  • Comprehensive health coverage.
  • Flexible PTO.
  • Federal holidays off.
  • Tuition reimbursement.
  • Professional development support.
  • Wellness stipends.
  • Remote work environment.

Interested in this position?

Apply directly on the company website

Apply Now

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