Senior Data Science Engineer — Healthcare RCM

Clarify AI; United States; Hybrid; USD 150,000 - 190,000; Full time

Job summary

Clarify AI is seeking a Senior Data Science Engineer to drive ML models and data solutions for Revenue Cycle Management in healthcare, with remote US-based work. You will build scalable models, develop predictive analytics, and integrate diverse healthcare data to improve billing processes and reduce denials.

The role emphasizes collaboration with product and engineering teams to deploy production-ready solutions and provide real-time insights across the revenue cycle.

Qualifications

• 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 (Hadoop, Spark).
• Experience with healthcare data standards (HL7, FHIR, X12) and integration practices.
• Strong background in NLP and predictive modeling.
• Knowledge of healthcare billing processes and revenue cycle operations.

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.

Skills

NLP

Predictive modeling

Healthcare domain knowledge

Python

SQL

HL7

FHIR

X12

Communication

Education

Master's or PhD in Computer Science / Data Science or related field

Tools

Hadoop

Spark

Job description

Senior Data Science Engineer — Healthcare RCM

Data Science Remote — U.S. Full Time

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.

• 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.