Senior Health Informatics Data Scientist

Role: Senior Health Informatics / Data Scientist Location: Remote (U.S.) Duration: 6+ Month Contract Working Time Zone: PST (Pacific Time Zone)

Position Overview

We are seeking a Senior Health Informatics / Data Scientist with deep technical expertise in statistical modeling, machine learning, and healthcare data analytics. This is a hands-on role focused on developing data science models using Python to support risk stratification and risk tier migration initiatives within the U.S. healthcare ecosystem .

The ideal candidate will have experience working with healthcare claims and population health datasets , building predictive models that support patient risk identification and care management strategies. The role requires strong familiarity with Medicare, Medicaid, and other U.S. healthcare reimbursement structures and coding frameworks .

This individual will collaborate with analytics, clinical, and population health teams to develop models that help identify high-risk populations and support value-based care initiatives.

Key Responsibilities

• Develop and implement statistical and machine learning models for healthcare risk stratification and population health analytics.
• Build predictive models to support risk tier migration and risk adjustment strategies .
• Use Python and modern data science libraries (pandas, NumPy, scikit-learn, etc.) to design, test, and deploy analytical models.
• Analyze large-scale healthcare datasets including claims, clinical, and demographic data .
• Work with healthcare stakeholders to translate analytical findings into actionable insights for care management and population health initiatives .
• Identify high-risk patient cohorts and support targeted intervention strategies.
• Ensure models and analytics align with Medicare, Medicaid, and other reimbursement frameworks .
• Document methodologies and present insights to both technical and non-technical stakeholders.

Required Qualifications

• Advanced degree in Data Science, Statistics, Biostatistics, Computer Science, Health Informatics, or related quantitative field.
• Strong experience in statistical modeling, machine learning, and predictive analytics .
• Hands-on Python programming experience for data science and model development.
• Experience working with healthcare claims data, population health data, or clinical datasets .
• Demonstrated experience with risk stratification, risk adjustment, or population health modeling .
• Strong analytical and problem-solving skills.

Preferred Qualifications

• Experience with risk tier migration analytics within healthcare organizations or health plans .

Familiarity with Medicare and Medicaid reimbursement structures .

Knowledge of healthcare coding standards such as ICD, CPT, and