Technical Analytics Manager/Lead Data Scientist

Position: Technical Analytics Manager/Lead Data Scientist

Location: Remote, with occasional site visits to PRAC locations as required

Work Environment: Remote
Clearance Required: Public Trust (HSPD-12)

Status: Contingent Upon Contract Award

Salary Range: $155,000 – $200,000 per year

Knowesis, Inc. is seeking a highly experienced Technical Analytics Manager/Lead Data Scientist to lead a multidisciplinary team providing end-to-end analytic and investigative support to the Pandemic Response Accountability Committee (PRAC). The PRAC delivers data-driven oversight of pandemic relief and OBBBA Act funds, supporting fraud prevention and detection efforts across federal programs. As an independent oversight committee within the Council of the Inspectors General on Integrity and Efficiency (CIGIE), the PRAC works closely with federal Offices of Inspectors General (OIGs) and federal law enforcement to ensure pandemic-related funding is used appropriately and not subject to fraud, waste, or abuse.

The Technical Analytics Manager/Lead Data Scientist will support the PRAC Analytics Center in conducting data analysis and visualization; sharing leading data analytics practices; providing tools and services; and providing investigative intelligence. The PRAC analytic platform develops analytic tools and products in its cloud-based environment. The PRAC currently uses Azure Databricks, Microsoft SQL Server, Microsoft Power BI, neo4j and other tools and technology to analyze and visualize public, non-public and commercially available data and to provide insights. The PRAC analytics platform operates through a series of agile sprints working with other PRAC internal stakeholder teams via Integrated Project Teams (IPT), and in a manner that uses business and service delivery models that will optimize its ability to scale up or down based on OIG community user demands.

The Job Duties and Responsibilities include but are not limited to the following:

• Lead and mentor a multidisciplinary team of data scientists, analysts, statisticians, and data engineers.
• Ensure analytic integrity, reproducibility, and compliance across all technical workstreams.
• Communicate complex analytic concepts to senior PRAC leadership, OIG partners, and non-technical stakeholders in clear, actionable terms.
• Oversee risk management, quality assurance, and performance monitoring for all analytic and investigative support activities.
• Foster innovation, continuous improvement, and adoption of best practices in fraud analytics and investigative data science.
• Lead analytic support for investigative case development using open-source, law enforcement, and third-party data sources.
• Produce customized investigative work products such as intelligence reports, link analysis diagrams, entity relationship charts, and fraud scheme visualizations.
• Apply graph analytics (including neo4j) to analyze complex networks and visualize relationships across multi-agency datasets.
• Conduct due diligence and verification of PRAC-developed analytic rules and model outputs to support investigative lead generation.
• Collaborate with OIGs and federal law enforcement partners following CIGIE/PRAC policies for handling law-enforcement-sensitive data.
• Present findings, investigative leads, and analytic insights to OIG and law enforcement stakeholders through briefings, demonstrations, and technical walkthroughs.
• Ensure investigative support workflows, templates, and documentation meet PRAC standards for accuracy, clarity, and evidentiary integrity.
• Conduct market research on emerging analytic tools, AI/ML technologies, data sources, and fraud detection capabilities; provide recommendations aligned with PRAC mission needs and federal policy.
• Collaborate with PRAC’s OCIO, OCISO, and OCDO to evaluate, configure, and integrate approved tools into the PRAC analytic environment.
• Develop iterative implementation plans for new capabilities, ensuring smooth integration, configuration, and operational readiness.
• Support ingestion of new data sources, including schema design, transformation logic, and quality control processes.
• Assist PRAC in evaluating cutting-edge AI and IT tools, providing technical analysis, documentation, and risk considerations to support Government procurement decisions.
• Maintain awareness of emerging fraud schemes, analytic technologies, and cross-program risks to inform future capability development.

Required Qualifications:

• Five (5) or more years of hands-on experience developing analytic rules and models for fraud detection use cases using leading-edge analytic tools, open-source programming techniques, and industry best practices.
• Five (5) or more years of experience designing analytic approaches, managing model development lifecycles, conducting model testing, and performing thorough quality control and validation.
• Demonstrated experience ideating and shaping analytic use cases using innovative approaches to detect and prevent fraud, waste, abuse, and mismanagement.
• Five (5) or more years of experience tracking project progress, identifying risks and issues, and implementing mitigation strategies to ensure timely, high-quality delivery of analytic projects.
• Five (5) or more years of experience conducting detailed review and quality control of contractor or team work products prior to finalizing analytic models, outputs, and insights.
• Five (5) or more years of hands-on coding experience developing analytic rules, models, and pipelines using open-source programming languages and tools (e.g., Python, R, SQL, Spark, etc.).
• Strong oral and written communication skills, including the ability to explain complex analytic concepts to senior leaders, investigators, and non-technical stakeholders.
  

Preferred Qualifications:

• Experience supporting fraud analytics, program integrity, or investigative support within federal oversight environments (e.g., OIGs, law enforcement, PRAC, CIGIE).
• Experience integrating multi-agency or multiprogram datasets to detect complex, emerging fraud schemes in high-risk or time-sensitive environments.
• Experience with graph analytics platforms (e.g., neo4j) and link analysis techniques for identifying hidden relationships and cross-program risks.
• Experience developing or deploying AI/ML models in compliance with federal AI governance frameworks (OMB M-25-22, M-25-21, M-26-04; NIST AI RMF).
• Experience leading or mentoring multidisciplinary analytic teams (data scientists, statisticians, engineers).
• Experience supporting enterprise data management (EDM), data governance, or federal data quality standards.
• Advanced certifications in data science, fraud examination, or analytics (e.g., CFE, Certified Data Scientist, AWS/Azure ML certifications).

Required Education: Bachelor’s degree (BA/BS) in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, or a related quantitative field. Advanced degree preferred.

Knowesis is committed to providing equal employment opportunities to all individuals based on merit and qualifications. We prohibit discrimination in all aspects of employment as required by Title VII of the Civil Rights Act and other applicable federal laws. Our company values all applicants and employees and fosters a work environment where everyone is treated with respect and dignity.