Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from The Association of Technology, Management and Applied Engineering
Position Summary
We’re building a world of health around every individual - shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger - helping to simplify health care one person, one family and one community at a time.
CVS Health’s Analytics & Behavior Change (A&BC) team is an organization working to solve some of the most challenging problems at the intersection of technology and healthcare. A&BC leverages advanced analytics, clinical informatics, and hypothesis‑driven approaches to transform data into actionable, customer‑centric insights that drive growth, improve health outcomes, and expand access to healthcare across all CVS Health businesses. Our teams build next‑generation data and AI products that help power CVS Health to make healthier happen for 100+ million customers.
The A&BC organization is looking to grow its Clinical Data Science & AI team. Join us as we embark on an exciting journey to drive a transformational shift in how CVS Health leverages clinical data and analytics to become the leader in consumer healthcare in the U.S.
As a Lead Decision Scientist - Patient Insights Optimization
, you will be tasked with understanding and quantifying the impact of clinical data on applications across CVS and Aetna. Your work will expose you to both the breadth and depth of uses of clinical data, and will inform strategic decisions about which investments in data CVS will make.
You will:
- Oversee multiple concurrent analytics projects in the field of healthcare and clinical data, ensuring a high standard of analytical rigor and execution.
- Provide technical leadership to a team of data and decision scientists, including setting standards for code quality, code review, and testing, while still remaining deeply embedded in the analytical work itself.
- Define a roadmap that delivers ongoing value to stakeholders while at the same time investing in maturing analytics engineering practices to scale the team’s efforts.
- Partner with product owners to design effective and creative analytical solutions to business needs, and with Engineering to efficiently product ionize these solutions.
- Use advanced statistics and mathematics judiciously where it solves critical business problems.
- Communicate technical concepts to a range of audiences, including business leaders, using effective storytelling and data visualization where its helpful.
- Uphold a high standard of documentation for both the team’s impact and its analytical foundation.
Required Qualifications
- 7+ years of relevant analytics experience.
- A track record of leading analytics projects from concept to delivery while coordinating across a diverse set of stakeholders.
- Knowledge of engineering best practices for analytics, including version control, testing, and CI/CD.
- Strong proficiency with SQL, including writing efficient, well‑structured queries and developing maintainable analytical data pipelines.
- Experience using at least one of the leading cloud platforms (GCP, AWS, Azure), and knowledge of best practices around data governance.
- Proficiency with Python, including aspects like dependency management and testing, as well as standard DS libraries like Num Py, pandas, and polars.
- Strong written and verbal communication skills, including the ability to present complex ideas to various audiences.
Preferred Qualifications
- Deep expertise in the healthcare domain and clinical data, including familiarity with FHIR and CCDA.
- Experience advocating for and establishing engineering best practices in analytics teams.
- Familiarity with Google Cloud Platform (GCP) tools, including Big Query and Vertex AI.
- Hands‑on experience with tools for the creation and management of complex analytic projects such as dbt, Airflow, and Cloud Composer.
- Training in advanced statistics, machine learning, and optimization.
Education Requirements
- Bachelor’s degree or equivalent work experience in Mathematics, Statistics, Computer Science, Business Analytics,…
Source: The Association of Technology, Management and Applied Engineering careers