Fraud Waste and Abuse Data Analyst

HHAeXchange is the leading technology platform for home and community-based care. Founded in 2008, HHAeXchange was born out of an idea to create a fully comprehensive end-to-end homecare solution to help people who are aging or have disabilities thrive in their homes and communities. Our employees are passionate about transforming the healthcare space by building the only homecare ecosystem that fully connects patients, personal care providers, managed care organizations, and states. Today, HHAeXchange supports Medicaid home and community-based care (HCBS) programs across all 50 states. Following the acquisition of Sandata, the platform processes electronic visit verification (EVV), visit records, and billing data for a significant portion of Medicaid home care services in the United States. As Medicaid programs grow in scale and complexity, states and managed care plans face increasing pressure to ensure program integrity and protect public funds. HHAeXchange is expanding its Fraud, Waste, and Abuse (FWA) capabilities to help customers identify billing anomalies, improper payments, and potential fraud within their data. The Sr FWA Data Analyst will play a key role in building these capabilities by analyzing large healthcare datasets to identify suspicious billing patterns and translating those insights into scalable detection tools. Working closely with product, engineering, and payer stakeholders, this role will help shape how fraud detection is embedded within the HHAeXchange platform. The ideal candidate brings deep knowledge of Medicaid regulatory requirements, the end-to-end revenue cycle, and the operational realities of both payers and providers in the home and community-based care space. To perform this job successfully, an individual must be able to perform each essential job duty satisfactorily with or without reasonable accommodation. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This is a fully remote opportunity for candidates located in the EST or CST time zones within the US only. Essential Job Duties Data Analysis & Fraud Detection • Analyze Medicaid claims, visit, and billing datasets using SQL and other analytical tools. • Identify patterns and anomalies that may indicate fraud, waste, or abuse, including: • Visit overlaps and impossible or implausible service combinations • Inflated, duplicate, or unbundled billing • Provider billing spikes or outlier utilization patterns • Inconsistencies in electronic visit verification (EVV) data • Suspicious provider enrollment or credentialing indicators • Patterns indicative of upcoding, place-of-service manipulation, or beneficiary identity issues • Develop and refine detection queries and analytical logic that can be applied across datasets at scale. • Conduct proactive data analysis to identify emerging fraud patterns and program integrity risks. • Apply knowledge of the end-to-end revenue cycle - including claims submission, adjudication, remittance, and denial/appeal workflows - to contextualize billing anomalies and assess their integrity implications. AI & Advanced Analytics • Apply machine learning and AI techniques to fraud detection, including anomaly detection models, predictive risk scoring, and unsupervised clustering of suspicious billing behavior. • Collaborate with data science teams on feature engineering, model validation, and the operationalization of AI-driven detection logic. • Leverage generative AI and LLM-based tools to support investigation summarization, pattern narrative development, and analytical workflow acceleration. • Stay current on emerging AI/ML applications in healthcare payment integrity and recommend adoption of relevant tools and techniques. • Test, validate, and continuously improve fraud detection models and analytical tools as they are developed and refined. Product & Engineering Collaboration • Translate analytical findings into clear, actionable requirements for product and engineering teams. • Contribute to the design of fraud detection dashboards, alerting systems, and investigation workflows. • Support the development of automated detection tools and AI-driven fraud identification capabilities. • Serve as a subject matter expert on FWA and program integrity concepts to ensure detection logic is clinically and operationally sound. Client & Stakeholder Engagement • Present analytical findings and insights to internal stakeholders and payer clients - including state Medicaid agencies and managed care organizations - in a clear and actionable format. • Support client discussions related to fraud detection strategy, program integrity reporting, and regulatory compliance obligations. • Advise payer and state partners on detection methodologies aligned with CMS program integrity expectations, Medicaid Integrity Program (MIP) standards, and applicable federal regulations. • Document analytical methodologies an...