Technical Analytics Manager / Lead Data Scientist

At Ardent, we hire people who want more than a job — they want to serve a mission that matters. Our teams support the federal government’s most critical national security and defense priorities, helping protect the nation, strengthen resilience, and advance the technologies and capabilities that keep America secure. For veterans, cleared professionals, and purpose-driven innovators, Ardent is a place to continue serving alongside a team that understands the importance of the mission and the people behind it.

We also know top talent has choices, which is why we back our mission with benefits and flexibility that stand out: competitive pay, comprehensive health coverage, flexible PTO, federal holidays off, tuition reimbursement, professional development support, wellness stipends, and a culture that values and rewards hard work, dedication, and adaptability. If you want to build something meaningful, while enjoying the kind of flexibility and support that you need to do your best work — Ardent is where your next mission begins.

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.

• →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 to support data ingestion, preparation, governance, quality, and lineage.
• →Develop and maintain technical documentation describing methodologies, data sources, model designs, assumptions, findings, and limitations.
• →Present analytical findings, technical recommendations, and project updates to technical and non-technical stakeholders.
• →Provide technical leadership, mentoring, and guidance to data scientists, analysts, and other project personnel.

Requirements: 

• →Minimum of 5 years of hands-on experience developing analytic rules and models for fraud detection, fraud prevention, waste and abuse detection, investigative analytics, or related use cases.
• →Minimum of 5 years of hands-on experience designing analytic approaches, managing model development and testing efforts, and conducting quality-control reviews.
• →Experience identifying use cases involving innovative approaches to detect and prevent fraud, waste, abuse, or mismanagement.
• →Minimum of 5 years of experience tracking project progress and identifying and mitigating risks and issues associated with analytics projects.
• →Minimum of 5 years of experience conducting technical reviews and quality-control reviews of contractor or project-team work products before delivery.
• →Minimum of 5 years of hands-on experience coding analytic rules and models using open-source programming technologies and tools.
• →Experience developing and validating predictive models, anomaly detection solutions, risk models, or other advanced analytics capabilities.
• →Experience working with complex, large-scale, structured and unstructured datasets.
• →Experience with Python, R, SQL, or comparable analytics and programming technologies.
• →Experience supporting data preparation, feature engineering, model evaluation, and performance monitoring activities.
• →Experience communicating analytical methods, findings, limitations, and recommendations to technical and non-technical audiences.
• →Strong leadership, analytical, problem-solving, and project-management skills.
• →Strong written and verbal communication skills.
• →Ability to successfully complete and maintain the required government background investigation.

Preferred Qualifications: 

• →Experience supporting federal fraud prevention, program-integrity, investigative, or oversight initiatives.
• →Experience working with Offices of Inspectors General, law enforcement organizations, or federal benefit programs.
• →Experience developing analytics solutions involving artificial intelligence, machine learning, natural language processing, graph analytics, or generative AI.
• →Experience with entity resolution, relationship analysis, identity matching, or risk scoring.
• →Experience with Azure Databricks, Microsoft SQL Server, Microsoft Power BI, Neo4j, or similar platforms.
• →Experience deploying and maintaining analytics solutions within cloud-based or enterprise data environments.
• →Experience supporting model governance, explainability, validation, auditability, and ongoing performance monitoring.
• →Experience mentoring or leading teams of data scientists, analysts, or technical specialists.
• →Master’s degree or higher in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related field.

Due to the nature of the work we support, all candidates in consideration for this role must be willing to undergo the government issued background investigation process. We highly encourage all Veterans and those with disabilities to apply.

Ardent is an equal opportunity employer. We will not discriminate in employment, recruitment, advertisements for employment, compensation, termination, upgrading, promotions, and other conditions of employment against any employee or job applicant on the bases of race, color, gender, national origin, age, religion, creed, disability, veteran's status, sexual orientation, gender identity, gender expression, or any other basis protected by state, local, or federal law.