Decision Scientist

CVS Health•Work At Home-Massachusetts, MA

1d•$79,310 - $158,620•Onsite

About The Position

The UM Analytics team provides data-driven insights that directly influence clinical and operational decision-making across Aetna's Utilization Management organization. We partner with Medical Affairs leadership, Medical Directors, and operational teams to evaluate care models, identify cost and quality improvement opportunities, and translate complex healthcare data into actionable recommendations. This Decision Scientist will join the Medical Affairs analytics pod, supporting senior analysts and stakeholders in delivering data analyses across a range of Medical Affairs projects. You will contribute to the analytics lifecycle — including data extraction, data validation, analysis execution, and results documentation — working under the guidance of the pod's lead analyst. This is a hands-on, execution-focused role ideal for someone early in their analytics career who is eager to build deep expertise in healthcare data, grow their stakeholder communication skills, and develop toward independent project ownership over time. You will collaborate with team members and cross-functional partners on analyses spanning areas such as care model performance evaluation, clinical program effectiveness, utilization trend analysis, and ad hoc exploratory research.

Requirements

1+ year of professional experience or internship experience in data analytics, decision science, or a quantitative role
Working proficiency in SQL for data extraction and manipulation (experience with BigQuery, Teradata, or similar platforms is a plus)
Familiarity with at least one programming language for data analysis (Python or R)
Experience working with large datasets and producing analytical outputs (reports, summaries, or visualizations)
Effective written and verbal communication skills — able to clearly document analytical methods and present findings to team members

Nice To Haves

Exposure to healthcare data (claims, clinical, enrollment, or similar) through coursework, internship, or prior employment
Familiarity with data visualization tools such as Tableau, Power BI, Looker, or similar
Interest in or foundational knowledge of managed care, health insurance, or utilization management concepts
Curiosity and willingness to learn new analytical methods, tools, and domain knowledge quickly
Ability to manage multiple tasks, meet deadlines, and communicate progress proactively
Experience with basic statistical analysis or coursework in statistics, econometrics, or related quantitative methods

Responsibilities

Contribute to the analytics lifecycle — including data extraction, data validation, analysis execution, and results documentation — working under the guidance of the pod's lead analyst.
Collaborate with team members and cross-functional partners on analyses spanning areas such as care model performance evaluation, clinical program effectiveness, utilization trend analysis, and ad hoc exploratory research.