项目完整性数据科学家 III
Program Integrity Data Scientist III
职位简介:
高级程序完整性数据科学家负责领导设计、开发和部署先进的分析解决方案,以支持支付准确性、异常检测以及欺诈、浪费和滥用(FWA)的预防和追回工作。该职位作为高级分析资源,为复杂的调查、预测建模计划和企业程序完整性策略提供技术领导,并指导初级分析师和数据科学家。
主要职责:
· 领导设计、开发和实施先进的算法,识别与潜在欺诈、浪费和滥用相关的支付前和支付后干预的索赔。
- 分析和量化支付问题,并提供缓解已识别程序完整性风险的建议。
- 在多个医疗数据集上识别新兴趋势、风险和模式,并推荐战略干预措施以改善程序完整性结果。
- 通过代码审查、分析审查和最佳实践建议,对分析师和数据科学家进行指导和技术支持。
- 评估新兴的分析、机器学习和AI技术,以提高欺诈检测、异常识别和支付完整性工作。
- 进行结果分析,以确定公司程序和支付完整性计划的影响和效果。
- 领导对复杂数据关系的检查和解释,以支持支付完整性、异常检测和FWA调查。
- 领导对与企业内潜在欺诈、浪费和滥用活动相关的异常和新兴趋势的监控和调查。
- 与法务部门合作,生成数据和分析以支持法律程序。
- 在统计有效的样本上进行假设检验和推断,以建立异常行为模式和潜在追偿。
- 领导开发和沟通针对复杂项目的分析策略、项目计划、方法和调查方法。
- 设计和开发高级仪表板、可视化和报告解决方案,以展示模型性能、项目有效性及程序完整性结果。
- 领导开发AI驱动和商业智能仪表板,以支持调查员工作流程、欺诈检测活动、运营监控和高管决策。
- 提供统计学方面的支持
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Job Summary:
The Program Integrity Data Scientist III is responsible for leading the design, development, and deployment of advanced analytical solutions that support payment accuracy, anomaly detection, and Fraud, Waste, and Abuse (FWA) prevention and recovery efforts. This role serves as a senior analytical resource, providing technical leadership across complex investigations, predictive modeling initiatives, and enterprise program integrity strategies while mentoring junior analysts and data scientists.
Essential Functions:
· 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.
Education and Experience:
· 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
Competencies, Knowledge and Skills:
· 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
Licensure and Certification:· None
Working Conditions:
· 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:
$94,100.00 - $164,800.00CareSource 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):
SalaryOrganization Level Competencies
- Fostering a Collaborative Workplace Culture
- Cultivate Partnerships
- Develop Self and Others
- Drive Execution
- Influence Others
- Pursue Personal Excellence
- Understand the Business
This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.
Brand=CareSourceOriginally posted on Himalayas