About The Position

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.

Requirements

  • 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.

Nice To Haves

  • Developing fraud detection, fraud prevention, and program integrity analytics supporting pandemic relief, emergency assistance, grants, loans, healthcare, unemployment insurance, disaster relief, financial assistance, or other high-volume federal benefit programs.
  • Designing, developing, validating, deploying, and maintaining advanced analytic models utilizing machine learning, artificial intelligence (AI), natural language processing (NLP), anomaly detection, entity resolution, graph analytics, link analysis, knowledge graphs, risk scoring, or robotic process automation (RPA).
  • Applying open-source programming languages and frameworks such as Python, SQL, Spark, Pandas, Scikit-learn, TensorFlow, PyTorch, or comparable data science technologies.
  • Developing analytics within cloud-native environments utilizing Azure Databricks, Microsoft SQL Server, Microsoft Fabric, Azure Data Lake, Power BI, Neo4j, Git repositories, Lakehouse architectures, or enterprise data catalogs.
  • Working with large-scale public, non-public, commercial, financial, and law enforcement datasets to identify organized fraud rings, synthetic identities, duplicate entities, eligibility issues, and emerging fraud schemes.
  • Conducting exploratory data analysis, data profiling, feature engineering, model validation, performance testing, and quality assurance throughout the analytics lifecycle.
  • Supporting Offices of Inspector General (OIGs), law enforcement organizations, oversight agencies, or program integrity initiatives through advanced analytic solutions.
  • Developing reproducible analytic workflows that emphasize governance, documentation, transparency, explainability, and enterprise data management best practices.
  • Leading technical reviews, mentoring data scientists, and establishing quality standards for analytic products delivered to Government customers.

Responsibilities

  • 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.

Benefits

  • Competitive salary based on qualifications and experience
  • Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)
  • 401(k) with company match
  • Travel & performance incentives
  • 3 weeks paid time off (plus Federal Holidays)
  • $5K annual training allowance
  • $500 book allowance
  • Tuition reimbursement program
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