Healthcare Revenue Data Scientist

• Building and deploying predictive models to assess anomalies and patterns in the Charge Capture process
• Developing and owning complex data products that can help automatically drive monthly financial close processes
• Conducting deep-dive analyses, heavy SQL coding, and predictive modeling to identify patterns in the data
• Partnering closely with the Operational Revenue Cycle team and Patient Financial Services to identify revenue leakage, audit aged Accounts Receivables, and track payer accountability.
• Building complex data models to assist leaders negotiating commercial insurance contracts and evaluate partner compliance.
• Working in a team, in partnership with several AI vendors, to develop, implement, and maintain advanced operational workflows to integrate vendor solutions.
• Serving as a liaison and communicator to leadership (department heads). This will include meeting regularly with business leaders to help solution how to embed automatic data processes into every day revenue cycle workflows

• Must be local to the NYC Metro area, and willing to work onsite at least 3 days /week
• Required Bachelor of Science Degree with 5-7+ years professional experience
• Preferred Master of Science in Math, Statistics, or Computer Science
• Must have at least 3 years of recent Healthcare Industry experience - Healthcare Revenue & Finance is highly preferred
• Expertise in Predictive Analytics
• Advanced hands-on experience with SQL
• Advanced hands-on experience with Python and Python-based libraries (PySpark, Numpy, SciPy)

No C2C Inquiries - this is a full time /permanent position.

Medix is currently seeking a Data Science Analyst for an exciting full-time opportunity with one of our Health System clients, headquartered in New York’s Upper East Side. This individual will be developing and operating / optimizing predictive models for deep analysis on the Health Systems’ financial / revenue cycle data, with an emphasis towards commercialization and cost-savings.