Technical Analytics Manager / Lead Data Scientist

Position Description

Ardent is seeking a Technical Analytics Manager / Lead Data Scientist to lead advanced analytics, artificial intelligence, and machine learning initiatives supporting fraud prevention, waste and abuse detection, investigative analysis, and program integrity within a federal environment. This role will provide technical leadership across analytics projects involving large and complex datasets, predictive modeling, anomaly detection, entity resolution, graph analytics, natural language processing, and data visualization. The Technical Analytics Manager / Lead Data Scientist will work closely with project leadership, government stakeholders, investigators, data engineers, and other technical personnel to develop, validate, and deploy defensible analytics solutions.

Responsibilities and Duties

• Lead the design, development, testing, validation, and deployment of advanced analytics and machine learning solutions.
• Manage analytics projects supporting fraud detection, fraud prevention, waste and abuse identification, and investigative activities.
• Develop and evaluate predictive models, anomaly detection methods, risk models, and entity-resolution techniques.
• Lead the development of analytics solutions using artificial intelligence, machine learning, natural language processing, graph analytics, and data visualization.
• Identify and refine analytics use cases in collaboration with government stakeholders, investigators, and program teams.
• Translate business, investigative, and operational requirements into technical analytics solutions.
• Lead technical discovery, data assessment, feature development, model selection, and solution design activities.
• Evaluate model performance, identify gaps, and recommend refinements or recalibration as needed.
• Ensure analytics models and outputs are accurate, explainable, defensible, repeatable, and aligned with project objectives.
• Track project progress, risks, issues, dependencies, and quality-control activities.
• Conduct technical reviews and quality-control reviews of analytics work products before delivery.
• Review code, models, documentation, data transformations, and analytic outputs for accuracy and completeness.
• Support the deployment, monitoring, maintenance, and ongoing improvement of analytics models in production environments.
• Collaborate with data engineers and data-management teams.