Machine Learning Engineer – Medical Billing/Reimbursement

We are looking for a Machine Learning Engineer to help us revolutionize the medical billing and reimbursement process. In this role, you will develop and deploy advanced machine learning models that identify billing discrepancies, optimize claims processing, and improve reimbursement accuracy. You will work with both structured and unstructured healthcare data, applying NLP and ML techniques to automate and enhance critical workflows in the healthcare billing system.

• Develop and deploy ML models to identify billing discrepancies, optimize claims processing, and improve reimbursement accuracy.
• Work with structured and unstructured healthcare data (e.g., claims data, EHR records, provider/payor transactions) to build robust models.
• Build and refine NLP models for interpreting medical codes and automating the claim validation process.
• Optimize algorithms for scalability and ensure real-time processing capabilities for medical claims.
• Ensure compliance with healthcare regulations (e.g., HIPAA, FHIR, HL7) to safeguard patient data and meet industry standards.
• Collaborate with cross-functional teams to integrate ML solutions seamlessly into production systems and workflows.

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field (PhD is a plus).
• 3+ years of experience in machine learning, AI, or data science, with a focus on healthcare applications.
• Experience with healthcare data (e.g., claims data, medical records) and NLP techniques for medical billing, coding, or clinical data processing.
• Familiarity with cloud platforms (AWS, GCP, Azure) for building scalable ML solutions.
• Strong programming skills in Python and experience with ML frameworks like TensorFlow, PyTorch, or HuggingFace.
• Knowledge of healthcare regulations (e.g., HIPAA) and standards like FHIR and HL7.