Program Integrity Data Scientist III - Experience supporting payment integrity, fraud detection, audit recovery, SIU, or program integrity initiatives preferred

• Lead the design, development, and implementation of advanced algorithms that identify claims for pre- and post-payment intervention related to potential Fraud, Waste, and Abuse.
• Analyze and quantify claim payment issues and provide recommendations to mitigate identified program integrity risks.
• Identify emerging trends, risks, and patterns across multiple healthcare datasets and recommend strategic interventions to improve program integrity outcomes.
• Mentor and provide technical guidance to analysts and data scientists through code reviews, analytical reviews, and best practice recommendations.
• Evaluate emerging analytical, machine learning, and AI techniques to improve fraud detection, anomaly identification, and payment integrity efforts.
• Conduct outcome analyses to determine impact and effectiveness of corporate program and payment integrity initiatives.
• Lead the examination and interpretation of complex data relationships to support payment integrity, anomaly detection, and FWA investigations.
• Lead monitoring and investigation of anomalies and emerging trends associated with potential Fraud, Waste, and Abuse activities across the enterprise.
• Collaborate with the legal department, generating data and analyses to support legal proceedings.
• Develop hypothesis tests and extrapolations on statistically valid samples to establish outlier behavior patterns and potential recoupment.
• Lead development and communication of analytical strategies, project plans, methodologies, and investigative approaches for complex initiatives.
• Design and develop advanced dashboards, visualizations, and reporting solutions that demonstrate model performance, program effectiveness, and program integrity outcomes.
• Lead development of AI-enabled and business intelligence dashboards that support investigator workflows, fraud detection activities, operational monitoring, and executive decision-making.
• Provide statistical validation and analysis of outcomes associated with clinical programs and interventions.
• Provide technical leadership in integrating analytical solutions with enterprise systems, platforms, and operational workflows.
• Present analytical findings, strategic recommendations, and program integrity insights to leadership and key stakeholders.
• Lead preparation and deployment of production-ready analytical code, models, and automated decision-support solutions.
• Research policy, billing guidelines, CMS direction and others to ideate new fraud, waste and abuse concepts to implement.
• Perform any other job related duties as requested.

• Bachelor's degree in Data Science, Mathematics, Statistics, Engineering, Computer Science, or a related field required
• Equivalent years of relevant work experience may be accepted in lieu of required education
• Five (5) years data analysis and/or analytic programming required
• One (1) year Experience with cloud services (such as Azure, AWS or GCP) and modern data stack (such as Databricks or Snowflake) preferred
• Healthcare experience required
• Experience supporting payment integrity, fraud detection, audit recovery, SIU, or program integrity initiatives preferred
• Experience developing and applying deep learning, neural network, graph analytics, or graph neural network (GNN) solutions for fraud detection, anomaly identification, payment integrity, or healthcare analytics initiatives preferred

• Advanced proficiency in SQL and at least one programming language such as Python or R
• Familiarity with SAS is preferred
• Proficient in designing and developing dashboards and reporting solutions using Power BI or similar business intelligence platforms
• Ability to perform advanced statistical analyses and techniques including t-tests, ANOVAs, z-tests, statistical extrapolations, non-parametric significance testing, and sampling methodologies
• Advanced knowledge of predictive modeling, machine learning, deep learning, neural networks, graph analytics, graph neural networks (GNNs), clustering, dimensionality reduction, anomaly detection, and natural language processing
• Proficient in feature engineering techniques and exploratory data analysis
• Ability to apply advanced analytical, artificial intelligence, and graph-based techniques to identify complex provider, member, claim, and organizational relationships associated with payment integrity, Fraud, Waste, and Abuse (FWA), anomaly detection, and recovery opportunities
• Ability to analyze large quantities of information and identify patterns, irregularities, and deficiencies
• Strong knowledge of healthcare coding, billing processes, reimbursement methodologies, claims adjudication and Program Integrity concepts.
• Proficient with MS office (Excel, PowerPoint, Word, Access)
• Demonstrated critical thinking, verbal communication, presentation and written communication skills
• Ability to independently lead analytical initiatives and collaborate effectively across cross-functional teams
• Familiarity with developing AI-enabled analytical solutions supporting fraud detection, anomaly identification, and payment integrity operations
• Ability to mentor analysts and data scientists through analytical reviews, statistical guidance, and technical coaching

• None

• General office environment; may be required to sit or stand for extended periods of time
• Up to 15% (occasional) travel to attend meetings, trainings, and conferences may be required

Compensation Range:

CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package.

Compensation Type (hourly/salary):

Organization Level Competencies

• Fostering a Collaborative Workplace Culture

• Cultivate Partnerships

• Develop Self and Others

• Drive Execution

• Influence Others

• Pursue Personal Excellence

• Understand the Business