Job Title

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 VHT’s 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 VHT’s 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 Additionally, we will work on emerging areas and integration opportunities—for example, denial prediction + appeal success probability or prior authorization prediction + approval likelihood models. You will reimagine how providers, patients, and payors interact within the healthcare ecosystem through intelligent automation and predictive insights, ensuring that providers can focus on delivering the highest quality patient care. VHT Technical Environment • Cloud Platform : AWS (SageMaker, S3, Redshift, EC2) • Development Tools : Jupyter Notebooks, Git, Docker • Programming : Python, SQL, R (optional) • ML/AI Stack : Scikit-learn, TensorFlow/PyTorch, MLflow, Airflow • Data Processing : Spark, Pandas, NumPy • Visualization : Matplotlib, Seaborn, Plotly, Tableau 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