Senior Healthcare Data Scientist & AI Solutions Leader

Insight Global; Hartford (CT); On-site; USD 130,000 - 180,000; Full time

Job summary

Insight Global is seeking a Senior Data Scientist to lead analytical initiatives addressing healthcare and Medicare challenges. You will define strategies, guide advanced statistical and ML approaches, and integrate complex data sources to explain member outcomes.

You will advise stakeholders on intervention design, ROI, and prioritization, communicating findings clearly to executives. The role requires reproducibility, data quality discipline, and collaboration across cross-functional teams.

Qualifications

• Master's degree in a data science or related field.
• 3–8 years of hands-on data science experience in a business setting.
• Experience building predictive and ML models.
• Excellent communication with technical and non-technical stakeholders.
• Experience in healthcare space.
• Hands-on Gen AI / LLM work.
• Production ML and MLOps experience.
• Experience with Medicare programs, member experience or clinical domains.

Responsibilities

• Lead analytical initiatives addressing healthcare and Medicare challenges with measurable impact.
• Define analytical strategies and direct advanced statistical and ML approaches.
• Integrate diverse data sources and model outputs to explain key outcomes.
• Advise stakeholders on interventions, ROI, and prioritization with executive-ready communication.

Skills

Python

SQL

Cloud experience

Communication

Gen AI / LLM

Production ML / MLOps

Tableau/Power BI

Healthcare domain

Medicare knowledge

Education

Masters

Tools

Tableau

Power BI

Cloud platforms (AWS/Azure)

ML frameworks (TensorFlow/PyTorch)

Job description

Insight Global is seeking a Senior Data Scientist to lead analytical initiatives addressing healthcare and Medicare challenges. You will define strategies, guide advanced statistical and ML approaches, and integrate complex data sources to explain member outcomes.

You will advise stakeholders on intervention design, ROI, and prioritization, communicating findings clearly to executives. The role requires reproducibility, data quality discipline, and collaboration across cross-functional teams.