Technical Analytics Manager – Lead Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the design, development, testing, validation, and implementation of sophisticated analytics and machine learning solutions.

• Manage analytics initiatives focused on fraud detection, fraud prevention, waste and abuse identification, and investigative efforts.

• Create and assess predictive models, anomaly detection techniques, risk models, and entity-resolution methods.

• Spearhead the creation of analytics solutions leveraging artificial intelligence, machine learning, natural language processing, graph analytics, and data visualization.

• Collaborate with government stakeholders, investigators, and program teams to identify and refine analytics use cases.

• Convert business, investigative, and operational requirements into technical analytics solutions.

• Direct technical discovery, data evaluation, feature development, model selection, and solution design processes.

• Assess model performance, pinpoint gaps, and suggest necessary refinements or recalibrations.

• Ensure that analytics models and outputs are accurate, explainable, defensible, repeatable, and aligned with project goals.

• Monitor project progress, risks, issues, dependencies, and quality-control measures.

• Execute technical reviews and quality-control evaluations of analytics deliverables prior to delivery.

• Review code, models, documentation, data transformations, and analytic outputs for precision and completeness.

• Assist in the deployment, monitoring, maintenance, and continuous enhancement of analytics models in live environments.

• Work in conjunction with data engineers and data-management teams to facilitate data ingestion, preparation, governance, quality, and lineage.

• Create and sustain technical documentation outlining methodologies, data sources, model designs, assumptions, findings, and limitations.

• Communicate analytical results, technical advice, and project updates to both technical and non-technical stakeholders.

• Provide technical leadership, mentorship, and guidance to data scientists, analysts, and other project team members.

⛳️ Requirements

• At least 5 years of hands-on experience in developing analytic rules and models for fraud detection, fraud prevention, waste and abuse detection, investigative analytics, or similar use cases.

• A minimum of 5 years of practical experience in designing analytic strategies, overseeing model development and testing processes, and performing quality-control evaluations.

• Proven experience in identifying use cases that utilize innovative methods for detecting and preventing fraud, waste, abuse, or mismanagement.

• Minimum of 5 years of experience in tracking project progress and identifying as well as mitigating risks and issues related to analytics initiatives.

• At least 5 years of experience in conducting technical evaluations and quality-control assessments of contractor or project-team deliverables before submission.

• Minimum of 5 years of hands-on experience in coding analytic rules and models using open-source programming technologies and tools.

• Experience in developing and validating predictive models, anomaly detection solutions, risk models, or other advanced analytics capabilities.

• Familiarity with complex, large-scale, structured, and unstructured datasets.

• Proficiency in Python, R, SQL, or similar analytics and programming technologies.

• Experience in assisting with data preparation, feature engineering, model evaluation, and performance monitoring tasks.

• Ability to convey analytical methods, results, limitations, and recommendations to both technical and non-technical audiences.

• Strong leadership, analytical, problem-solving, and project management skills.

• Excellent written and verbal communication abilities.

• Capability to successfully complete and maintain the necessary government background investigation.

🏝️ Benefits

• Competitive salary

• Comprehensive health insurance coverage

• Flexible paid time off (PTO)

• Federal holidays off

• Tuition reimbursement

• Support for professional development

• Wellness stipends

• A culture that appreciates and rewards hard work, dedication, and adaptability