Technical Analytics Manager​/Lead Data Scientist; Fraud Analytics & Investigative Support

Location: Remote (Occasional Travel May Be Required)

Clearance: Ability to obtain and maintain a Public Trust

Praescient Analytics is seeking a highly skilled Technical Analytics Manager / Lead Data Scientist to provide technical leadership for a federal fraud analytics and investigative support program. This individual will serve as the technical authority responsible for designing innovative analytic approaches, developing advanced fraud detection models, leading model validation and quality assurance activities, and ensuring the successful delivery of reliable, defensible, and repeatable analytic solutions supporting federal oversight organizations.

The ideal candidate is a hands‑on technical leader who combines deep data science expertise with strong leadership skills. They will guide multidisciplinary technical teams through the full analytics lifecycle, from ideation and data exploration to model development, testing, deployment, and continuous improvement, while mentoring technical staff and collaborating closely with Government stakeholders, investigators, and program leadership.

• Lead the design, development, testing, validation, deployment, and continuous improvement of advanced fraud detection and investigative analytics solutions.
• Develop innovative analytic approaches to identify fraud, waste, abuse, and mismanagement across large-scale federal benefit programs.
• Design and implement analytic rules, machine learning models, artificial intelligence (AI) solutions, natural language processing (NLP), anomaly detection, entity resolution, graph analytics, link analysis, risk scoring, and other advanced analytic capabilities.
• Lead technical teams responsible for model development, experimentation, quality assurance, documentation, and production deployment.
• Perform hands‑on development of analytic models using open‑source programming languages, frameworks, and data science tools.
• Conduct exploratory data analysis, feature engineering, data profiling, model evaluation, and performance optimization across complex datasets.
• Establish and oversee rigorous quality control processes to ensure analytic outputs are accurate, reliable, repeatable, and fully documented prior to Government delivery.
• Review technical work products, source code, analytic methodologies, and model outputs produced by contractor support teams.
• Identify technical risks, recommend mitigation strategies, and ensure timely delivery of high‑quality analytic products.
• Collaborate with Project Managers, Data Engineers, Graph Data Scientists, Investigative Analysts, Forensic Accountants, and Government stakeholders throughout the project lifecycle.
• Present analytic methodologies, technical findings, model performance, and recommendations to Government leadership, investigators, and oversight organizations.
• Support Agile delivery through sprint planning, backlog refinement, technical demonstrations, and iterative model development.

• Must have experience with Fraud Analysis
• Five (5) or more years of hands‑on experience developing analytic rules and models for fraud detection use cases using leading‑edge analytic tools and best practices.
• Five (5) or more years of experience designing analytic approaches, managing model development and testing efforts, and conducting thorough quality control.
• Demonstrated experience ideating innovative analytic use cases to detect and prevent fraud, waste, abuse, and mismanagement.
• Five (5) or more years of experience tracking project progress, identifying technical risks, and delivering high‑quality analytic solutions on schedule.
• Five (5) or more years of experience reviewing contractor‑developed analytic models, code, methodologies, and work products prior to final delivery.
• Five (5) or more years of hands‑on experience developing analytic rules and models using open‑source programming languages and frameworks.
• Strong written, verbal, presentation, and technical communication skills.
• Demonstrated ability to lead technical teams while remaining actively engaged in hands‑on analytics development.

Preference will be given to…