Sr. Data Scientist, Healthcare

Senior Data Scientist to join our healthcare analytics team. The ideal candidate will have a strong background in data science, with specific expertise in Health Equity and behavioral science. You will play a key role in analyzing complex healthcare data, developing predictive models, and providing actionable insights to improve healthcare outcomes, quality, and efficiency.

Role and Responsibilities:

• Analyze large and complex healthcare datasets to identify trends, patterns, and insights.
• Develop predictive models and algorithms to forecast healthcare outcomes, patient risks, and quality measures.
• Conduct advanced statistical analysis to support healthcare quality improvement initiatives.
• Lead the development and implementation of analytics solutions related to Health Equity.
• Collaborate with clinical and quality teams to enhance the accuracy and effectiveness of different plan measures.
• Provide strategic insights and recommendations to improve STARS ratings based on data analysis
• Strong experience working on US Healthcare industry - prior experience on Medicare STARS is preferred.
• Integrate and manage diverse healthcare data sources, including claims, benefits, and patient surveys.
• Ensure data integrity, quality, and accuracy in all analytics projects
• Work closely with cross-functional teams, including clinical, IT, and operations, to align data science efforts with organizational goals.
• Communicate complex analytical findings to non-technical stakeholders through clear and concise reports, visualizations, and presentations

Candidate Profile:

Required Qualification and Skills:

• Strong experience on Medical Insurance plans and claims for analyzing and maintaining Health Equity.
• 5-7 years of experience on Python, SQL and Tableau
• Experience with big data technologies (e.g., Hadoop, Spark) and cloud platform GCP
• Experience with DevOps practice, CI/CD pipelines
• Experience in Designing, developing, and deployment of advanced predictive models, machine learning algorithms, and statistical analyses to solve complex healthcare problems, such as patient risk prediction, treatment optimization, and resource allocation
• Excellent verbal and written communication skills, with the ability to convey complex information to diverse audiences.