Senior Data Scientist

Our client is a leading healthcare organization dedicated to improving patient outcomes through innovation, data-driven insights, and advanced technology. We leverage cutting-edge analytics, machine learning, and clinical data to transform care delivery, optimize operations, and support better decision-making across the healthcare ecosystem.

We are seeking a highly skilled and experienced Senior Data Scientist to join a growing data team. In this role, you will lead the development of advanced analytics and machine learning solutions that drive impactful healthcare outcomes. You will work with large, complex healthcare datasets including clinical, claims, and operational data to generate actionable insights and build predictive models.

This is a high-impact role requiring both technical expertise and strong collaboration with cross-functional teams, including clinicians, product managers, engineers, and business stakeholders.

• Design, develop, and deploy machine learning models and statistical analyses to solve complex healthcare problems.
• Analyze large-scale structured and unstructured datasets (e.g., EHRs, claims data, patient records) and lead end-to-end data science projects from problem definition to deployment and monitoring.
• Collaborate with clinical and business stakeholders to translate requirements into analytical solutions.
• Build predictive models for patient outcomes, risk stratification, resource utilization, and operational efficiency.
• Develop and maintain data pipelines and feature engineering processes.
• Communicate findings and insights clearly to both technical and non-technical audiences.
• Mentor junior data scientists and contribute to best practices across the team.
• Stay current with advances in healthcare analytics, machine learning, and regulatory considerations (e.g., HIPAA).

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (Master’s or PhD preferred).
• 5–8+ years of experience in data science, analytics, or machine learning roles.
• Strong programming skills in Python (preferred) or R.
• Expertise in machine learning, statistical modeling, and data analysis techniques.
• Experience working with healthcare data (EHR, claims, clinical trials, or similar).
• Proficiency with SQL and working with large datasets and distributed systems.
• Experience with data visualization tools (e.g., Tableau, Power BI, or similar).
• Strong problem-solving skills and ability to work independently.

• Advanced degree (MS or PhD) in a quantitative field.
• Experience building and deploying models in production environments (e.g., AWS, Azure, GCP).
• Knowledge of healthcare regulations and data privacy standards (HIPAA, HL7, FHIR).
• Familiarity with deep learning, NLP (especially clinical text), or time-series modeling.
• Experience with MLOps tools and frameworks.