Senior ML Engineer (Claim Scrubbing & Denial Prediction)

Experience: 5 – 9 Years Domain: Revenue Cycle Management (RCM) Location: Chennai Work Mode: Onsite (5 Days a Week) Role Overview We are seeking a Machine Learning Engineer with Healthcare RCM expertise to develop AIdriven solutions for Claims Scrubbing and Denial Prediction. The ideal candidate will leverage machine learning techniques and healthcare claims data to improve clean claim rates, reduce denials, and optimize reimbursement outcomes. Key Responsibilities • Develop and optimize machine learning models for denial prediction and claims risk scoring. • Build AI-powered claims scrubbing solutions using payer rules, edits, and historical claims data. • Analyze claims, denials, and reimbursement data to identify patterns and improve model accuracy. • Collaborate with RCM SMEs, billing teams, and product stakeholders to align AI solutions with business workflows. • Monitor model performance and continuously improve prediction accuracy through feedback and denial outcomes. • Ensure model explainability, traceability, and compliance with healthcare regulations. Key Skills • Strong experience in Python and Machine Learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. • Solid understanding of Healthcare Revenue Cycle Management (RCM) and denial management workflows. • Experience with Claims Scrubbing, Denial Prediction, and Revenue Integrity solutions. • Knowledge of EDI X12 healthcare transactions including 837, 835, 278, and 276/277. • Ability to handle and process healthcare claims data and transaction workflows. • Understanding of healthcare data standards including X12, HL7, and FHIR. • Ensure HIPAA compliance and secure handling of Protected Health Information (PHI). • Strong analytical, problem-solving, and data modeling skills. Preferred Qualifications • Bachelor's degree in engineering or a related technical discipline • Experience working on Healthcare AI, Claims, or RCM platforms. • Familiarity with payer edits, clearinghouse validations, and claim lifecycle management. • Exposure to Generative AI and AI-assisted healthcare workflows. • Experience with cloud platforms such as Azure, AWS, or GCP.