Senior Health Informatics / Data Scientist
About this role
Employer-provided description, formatted for easier reading.
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 HCPCS codes .
- Experience working with health plans, healthcare analytics firms, provider organizations, or consulting firms .
- Originally posted on Himalayas