Why This Role Stands Out
Leverage your expertise in Python and R to develop cutting-edge machine learning models for fraud detection within a leading healthcare analytics firm, enjoying a competitive salary and the flexibility of a 100% remote role. This contract-to-hire position is ideal for a mid-senior level data scientist with a passion for driving significant cost savings and shaping the future of healthcare revenue integrity. Apply today to make a substantial impact from anywhere in the US!
Quick Overview
Job Description
Job Title: Healthcare Revenue Data Scientist - 100% Remote
Position Type: Contract to Hire
Position Level: 3-5+ years post-graduate professional experience
Compensation Range: $125,000 - $150,000 / year
Work Location: FULLY REMOTE
*Must live in the US and work EST/CST hours
ABOUT OUR CLIENT / ABOUT THIS ROLE
Medix is currently seeking a Healthcare Revenue Data Scientist for a career opportunity with one of our Healthcare Analytics Services clients. This is a 100% remote role that will start on a contract basis (6-12 months), and convert to a full-time employee in 2027.
This Healthcare Revenue Data Scientist will be joining a team focused on developing Machine Learning Algorithms to predict Fraud, Waste and Abuse (FWA) across the Revenue Life Cycle. This individual will be developing and operating / optimizing predictive models for deep analysis on financial / revenue cycle data, with an emphasis towards identifying outliers and anomalies, and returning measurable cost-savings to healthcare clients.
Please note that a deep proficiency with Python, Python Libraries and Statistical language like R Programming are required.
RESPONSIBILITIES
- Building and deploying predictive models to assess anomalies and patterns for fraud, waste, and abuse in Healthcare Claims / Financial Data.
- Developing and owning complex data products that can help automatically identify and prevent FWA.
- Building end to end data pipelines (structured, text, documents, images) optimized for LLMs and multi-modal models.
- Designing, developing and deploying LLM-based solutions (RAG, embeddings, instruction tuning) for claims handling, document understanding, and related use cases.
- Conducting deep-dive analyses, heavy SQL coding, and predictive modeling to identify patterns in the data
- Working with Agentic AI tools to develop, implement, and maintain advanced operational workflows to integrate vendor solutions with client environments.
- 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
- Visualizing data via dashboards and present complex findings to non-technical stakeholders and/or legal teams
REQUIRED SKILLS
- Required Bachelor of Science Degree
- Must have at least 3 years of aligned experience in the Industry with Healthcare Billing and Revenue Cycle
- Strong background in applied statistics, regression analysis, and clustering techniques.
- Advanced hands-on experience with Python and Python-based libraries (PySpark, Numpy, SciPy)
- Advanced hands-on experience with SQL
No C2C Inquiries - this is a contract to hire a position that will convert to a full time employee within 6 months.
For California Applicants:
We will consider for employment all qualified Applicants, including those with criminal histories, in a manner consistent with the requirements of applicable federal, state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance (FCIHO), Los Angeles Fair Chance Ordinance for Employers (ULAC), The San Francisco Fair Chance Ordinance (FCO) , and the California Fair Chance Act (CFCA).
This position is subject to a background check based on its job duties, which may include patient care, working with vulnerable populations, access to financial and confidential information, driving, working with heavy machinery, or working in a warehouse or laboratory environment. Due to these job duties, this position has a significant impact on the business operations and reputation, as well as the safety and well-being of individuals who may be cared for as part of the job position or who may interact with staff or clients.
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