Program Integrity Data Scientist III

CareSource

. Lead the design, development, and implementation of advanced algorithms identifying claims for pre- and post-payment intervention related to potential Fraud, Waste, and Abuse .

Posted 9/23/2026full-timeRemote • United StatesMid-LevelSenior💰 $94,100 - $164,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced data analysis, machine learning, and fraud detection within healthcare, utilizing programming skills in SQL and Python. Capable of leading analytical initiatives, mentoring teams, and developing strategic recommendations based on data-driven insights.

Highest-signal resume keywords

Data AnalysisMachine LearningFraud DetectionSQL ProficiencyHealthcare Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Advanced Statistical AnalysisPredictive ModelingDeep LearningFeature EngineeringExploratory Data AnalysisGraph AnalyticsAnomaly DetectionStatistical ExtrapolationsCloud ServicesProgramming in Python

Soft Skills

Critical ThinkingVerbal CommunicationPresentation SkillsWritten CommunicationMentoring

Tools & Technologies

Power BIAzureAWSGCPDatabricksSnowflakeMicrosoft Office

Industry Keywords

FraudWasteAbusePayment IntegrityClaims AdjudicationHealthcare CodingBilling ProcessesAudit RecoveryProgram IntegrityStatistical Validity

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact

Lead the design, development, and implementation of advanced algorithms identifying claims for pre- and post-payment intervention related to potential Fraud, Waste, and Abuse
Analyze and quantify claim payment issues and recommend mitigations for program integrity risks
Identify trends, risks, and patterns across healthcare datasets and recommend strategic interventions
Mentor analysts and data scientists through code reviews, analytical reviews, and best-practice recommendations
Evaluate analytical, machine learning, and AI techniques for fraud detection, anomaly identification, and payment integrity
Conduct outcome analyses for corporate program and payment integrity initiatives
Lead complex data relationship analysis for payment integrity, anomaly detection, and FWA investigations
Monitor and investigate anomalies and emerging FWA trends across the enterprise
Collaborate with legal to generate data and analyses supporting legal proceedings
Develop hypothesis tests and extrapolations on statistically valid samples to establish outlier behavior and potential recoupment
Lead analytical strategies, project plans, methodologies, and investigative approaches
Design dashboards, visualizations, and reporting solutions demonstrating model performance and program outcomes
Develop AI-enabled and business intelligence dashboards supporting investigator workflows, fraud detection, operational monitoring, and executive decision-making
Provide statistical validation and analysis of clinical program and intervention outcomes
Integrate analytical solutions with enterprise systems, platforms, and operational workflows
Present analytical findings and strategic recommendations to leadership and stakeholders
Lead preparation and deployment of production-ready code, models, and automated decision-support solutions
Research policy, billing guidelines, and CMS direction to develop new fraud, waste, and abuse concepts

Requirements

What you’ll need

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 of data analysis and/or analytic programming required
Healthcare experience required
One (1) year of experience with cloud services such as Azure, AWS, or GCP and modern data stacks such as Databricks or Snowflake preferred
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 solutions preferred
Advanced proficiency in SQL and at least one programming language such as Python or R
Familiarity with SAS preferred
Proficiency designing and developing dashboards and reporting solutions using Power BI or similar platforms
Advanced statistical analysis skills, 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, clustering, dimensionality reduction, anomaly detection, and natural language processing
Proficiency in feature engineering and exploratory data analysis
Knowledge of healthcare coding, billing processes, reimbursement methodologies, claims adjudication, and program integrity concepts
Proficiency with Microsoft Office, including Excel, PowerPoint, Word, and Access
Critical thinking, verbal communication, presentation, and written communication skills
Ability to independently lead analytical initiatives and collaborate across cross-functional teams
Ability to mentor analysts and data scientists
No licensure or certification required

Benefits

Comp & perks

Bonus tied to company and individual performance may be available
Comprehensive total rewards package
Employee well-being support
Equal opportunity and belonging-focused workplace
Up to 15% occasional travel to meetings, trainings, and conferences