Description/Position Overview :

This is a key position for our client to help create data-driven technology solutions that will position us as the industry leader in healthcare, financial, and clinical administration.

This hands-on Lead Data Scientist role will focus on building and implementing machine learning models and predictive analytics solutions that will drive the new wave of AI-powered innovation in healthcare.

You will be the lead data science technologist responsible for developing and implementing a multitude of ML/AI products from concept to production, helping us gain a competitive advantage in the market.

Alongside our Director of Data Science, you will work at the intersection of healthcare, finance, and cutting-edge data science to solve some of the industry's most complex challenges.

This is a greenfield opportunity within VHTs Product Transformation division, where you'll build groundbreaking machine learning capabilities from the ground up.

You'll have the chance to shape the future of VHTs data science & analytics foundation while working with cutting-edge tools and methodologies in a collaborative, innovation-driven environment.

Key Responsibilities :

- As the Lead Data Scientist, your role will require you to work closely with subject matter experts in clinical and financial administration across practices, health systems, hospitals, and payors.

- Your machine learning projects will span the entire healthcare revenue cycle from clinical encounters through financial transaction completion, extending into back-office operations and payer interactions.

- You will lead the development of predictive machine learning models for Revenue Cycle Management analytics, along the lines of :

- Payer Propensity Modeling predicting payer behavior and reimbursement likelihood.

- Claim Denials Prediction identifying high-risk claims before submission.

- Payment Amount Prediction forecasting expected reimbursement amounts.

- Cash Flow Forecasting predicting revenue timing and patterns.

- Patient-Related Models enhancing patient financial experience and outcomes.

- Claim Processing Time Prediction optimizing workflow and resource allocation.

Required Qualifications :

- Advanced degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.

- 5+ years of hands-on data science experience with a proven track record of deploying ML models to production.

- Expert-level proficiency in SQL and Python, with extensive experience using standard Python machine learning libraries (scikit-learn, pandas, numpy, matplotlib, seaborn, etc.

- Cloud platform experience, preferably AWS, with hands-on knowledge of SageMaker, S3, Redshift, and Jupyter Notebook workbenches (other cloud environments acceptable).

- Strong statistical modeling and machine learning expertise across supervised and unsupervised learning techniques.

- Experience with model deployment, monitoring, and MLOps practices.

- Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders.

Preferred Qualifications :

- US Healthcare industry experience, particularly in Health Insurance and/or Medical Revenue Cycle Management.

- Experience with healthcare data standards (HL7, FHIR, X12 EDI).

- Knowledge of healthcare regulations (HIPAA, compliance requirements).

- Experience with deep learning frameworks (TensorFlow, PyTorch).

- Familiarity with real-time streaming data processing.

- Previous leadership or mentoring experience.