Remote Graph Data Scientist: Fraud Detection & Network Insights

Knowesis Inc.; Washington (District of Columbia); Remote; USD 125,000 - 165,000; Full time

Job summary

Knowesis, Inc. is seeking an experienced Graph Data Scientist to support the Pandemic Response Accountability Committee (PRAC) by developing graph-based analytics to detect fraud, waste, abuse, and mismanagement across federal programs.

The role involves building graph models, knowledge graphs, and link analysis tools in a cloud-based environment, using Azure Databricks, SQL Server, Power BI, and neo4j to drive actionable insights.

Responsibilities

• Develop graph-based analytic rules and models to detect fraud, waste, abuse, and mismanagement across multi-agency and multi-program datasets.
• Apply advanced graph theory concepts—network topology, centrality measures, community detection, and shortest-path algorithms—to identify hidden relationships and emerging fraud schemes.
• Use Neo4j (or similar graph databases) and fluently write Cypher queries to build, test, and optimize graph models and knowledge graphs supporting PRAC analytic use cases.
• Conduct exploratory data analysis and data profiling on public and non-public datasets to prepare graph structures and ensure high-quality ingestion.
• Apply clustering, classification, anomaly detection, and other ML techniques to graph-structured data to enhance fraud detection capabilities.
• Design, implement, and optimize graph data pipelines, schemas, and data models that support high-complexity networks and large-scale analytic environments.
• Document methodologies, graph models, code, and analytic outputs in accordance with PRAC data governance, EDM standards, and federal oversight requirements.
• Collaborate with PRAC stakeholders, OIG partners, and law enforcement to refine analytic approaches, validate graph-based findings, and support cross-program risk identification.
• Conduct graph-based investigative analysis using open-source, law enforcement, and third-party data to support lead generation and case development.
• Build link analysis diagrams, entity relationship charts, and graph-based intelligence products that visualize complex networks and relationships across multiple data sources.
• Use graph analytics to validate PRAC-developed analytic rules and model outputs, performing due diligence to confirm or refute potential fraud indicators.
• Support OIG and law enforcement partners by producing customized investigative work products and presenting graph-derived insights in clear, actionable formats.
• Follow PRAC investigative workflows, templates, and policies for handling law-enforcement-sensitive data and multi-agency investigative information.
• Evaluate emerging graph analytics tools, graph databases, and data sources; provide recommendations aligned with PRAC mission needs and federal policy.
• Collaborate with PRAC's OCIO, OCISO, and OCDO to configure, integrate, and optimize approved graph tools within the PRAC analytic environment.
• Support ingestion of new data sources into graph environments, including schema design, transformation logic, and quality control.
• Assist PRAC in analyzing cutting-edge graph-based AI/ML tools and technologies, providing technical documentation and risk considerations to support Government procurement decisions.
• Maintain awareness of evolving fraud schemes, graph analytic techniques, and cross-program risks to inform future cap
• }],
• CoT_job_summary_short
• job_summary_short
• <p>Knowesis, Inc. is seeking an experienced Graph Data Scientist to support the Pandemic Response Accountability Committee (PRAC) by developing graph-based analytics to detect fraud, waste, abuse, and mismanagement across federal programs. The role involves building graph models, knowledge graphs, and link analysis tools in a cloud-based environment, using Azure Databricks, SQL Server, Power BI, and neo4j to drive actionable insights.</p><p>Remote work with occasional site visits to PRAC locations is available; the position requires strong technical expertise, analytic rigor, and the ability to translate complex graph-based findings into clear intelligence for diverse stakeholders, including law enforcement and OIG partners.</p>
• contract_type
• fulltime
• location_type
• remote
• remote_scope
• national
• perks
• []
• stated_min
• 125000
• stated_max
• 165000
• stated_absolute
• null
• salary_estimation_cot
• Graph Data Scientist in the United States with Public Trust clearance: $125k-$165k per year; cloud-based tools and graph analytics drive fraud detection in PRAC.
• estimated_low
• 125000
• estimated_medium
• 145000
• estimated_high
• 165000
• currency
• USD
• frequency
• yearly
• bonus
• null
• tax
• gross
• application_email
• null
• job_end_date
• null
• contact_person
• null
• hiring_department_name
• PRAC Analytics Center

Job description

Knowesis, Inc. is seeking an experienced Graph Data Scientist to support the Pandemic Response Accountability Committee (PRAC) by developing graph-based analytics to detect fraud, waste, abuse, and mismanagement across federal programs.

The role involves building graph models, knowledge graphs, and link analysis tools in a cloud-based environment, using Azure Databricks, SQL Server, Power BI, and neo4j to drive actionable insights.