Senior Data Scientist – Clinical Analytics & Causal Inference

At CVS Health, we’re building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care.

As the nation’s leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. And we do it all with heart, each and every day.

A Brief Overview

Our team provides insights, designs personalized outreaches and nudges, and experiments at impressive scale: >100M messages per year. These messages educate members on truly meaningful things like staying adherent to medications, avoiding admissions to hospitals, and improving overall health.

We do this through a combination of rules, statistical, and ML models that identify who to target, an experimentation platform that we’ve built that allows complex journeys and test designs, and a combination of channels and vendors that deliver messages. We do this hand in hand with our data engineering, clinical, and marketing partners.

You will join a team that enables our clinical colleagues as they reach out to members with rare chronic diseases. You will work closely with the general business manager to ensure our solutions deliver value for our clients and continue to improve. You will have an opportunity to dive deep into the dynamics care management for rare chronic diseases and design a best-in-class solution that meets and supports members where they are on their health journey.

What you will do:

• Design, execute, and analyze experiments and quasi-experiments (e.g., A/B testing, differences-in-differences) to validate model impact and continuously improve business outcomes.
• Develop predictive models that identify high risk situations that warrant increased attention to avoid adverse outcomes such as hospitalizations.
• Evaluate and deploy genAI solutions that improve clinician workflows (e.g., call summarization and case prep summaries).
• Write complex and efficient code in SQL, Python or R and leverage Exploratory Data Analysis techniques to develop insights from multiple data sources in a cloud environment.
• Consults with internal clients to identify opportunities to implement data science solutions to business problems at an advanced level.
• Effectively collaborate with Data Engineering, IT and other technical teams to onboard new data sources, create feature stores and optimize/ automate model development and deployment processes (Github, MLOps etc.).
• Collaborate effectively with business, clinical, marketing, and other stakeholders across the organization.
• Present recommendations to senior staff and internal clients.
• Rapidly iterate through solutions to figure out what works best.
   

The ideal candidate:

• Has a deep understanding of causal inference methods (e.g., difference-in-differences, instrumental variables) and experimental design.
• Has a solid grasp of foundations and experience with predictive modeling and optimization methods with structured and unstructured data.
• Has some experience evaluating and deploying genAI solutions into clinician workflows.
• Wants to do something that is innovative from a data science perspective and provides tangible real-world impact.
• Is okay with ambiguity and can creatively build solutions that solve problems, even if those problems are not expressed in formal ways like BRDs.
• Has experience working as a social scientist and as a data scientist.
• Loves innovating and working on small teams that get stuff done and have a lot of autonomy.
• Healthcare background is a plus.
   

For this role you will need the following minimum requirements:

• Mastery of problem solving and decision-making skills
• Mastery of collaboration and teamwork
• Mastery of growth mindset (agility and developing yourself and others) skills
• Mastery of execution and delivery (planning, delivering, and supporting) skills
• 3+ years work experience (inclusive of applied research experience)
   

Programming/Technical skills required:

• Strong theoretical and hands-on experience with statistics and ma