Senior Data Science Engineer — Healthcare RCM

Job Description

We are looking for a Senior Data Science Engineer to drive the development of machine learning models and advanced data solutions that optimize Revenue Cycle Management (RCM) in healthcare. In this role, you will leverage cutting-edge technologies to improve billing processes, reduce claim denials, and enhance overall performance across the revenue cycle. You will work closely with cross-functional teams to build scalable solutions that process complex healthcare data and deliver actionable insights in real-time.

Roles & Responsibilities

• Develop advanced ML models to optimize revenue cycle management, focusing on automation and efficiency.
• Create algorithms for claim denial prediction and prevention, helping reduce inefficiencies in the billing process.
• Design NLP solutions for automating the analysis of medical documentation to streamline billing operations.
• Build data pipelines to process and integrate both structured and unstructured healthcare data for model training and analysis.
• Implement real-time analytics dashboards to provide visibility into revenue cycle performance and drive data-informed decision-making.
• Collaborate with product and engineering teams to deploy and maintain machine learning solutions in production environments.

Qualifications & Skills

• Master's or PhD in Computer Science, Data Science, or a related field.
• 5+ years of experience in machine learning and data engineering, preferably in healthcare applications.
• Proficiency in Python, SQL, and big data technologies (e.g., Hadoop, Spark).
• Experience with healthcare data standards (HL7, FHIR, X12) and integration practices.
• Strong background in Natural Language Processing (NLP) and predictive modeling.
• Knowledge of healthcare billing processes and revenue cycle operations, including claims processing, denials management, and reimbursement.

Location & Work Authorization

This is a U.S.-based role. Candidates must be located in the United States and authorized to work in the U.S. without current or future employment sponsorship.