Principal Data Scientist (Clinical Informatics)

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.

Position Overview

CVS Health’s Analytics & Behavior Change (A&BC) is an organization working to solve some of the most challenging problems at the intersection of technology and healthcare. A&BC leverages advanced analytics, machine learning, modeling, and a hypothesis-driven approaches to transform data into actionable, customer-centric insights to drive growth, improve health outcomes and access to health care across all our businesses in CVS Health. Our teams build next generation data and machine learning platforms and software 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 technology and analytics to become the leader in consumer healthcare in the U.S. In this role you will be tasked with activating CVS Health’s clinical data repository to improve outcomes across multiple lines of business and use cases. As a Principal Data Scientist, you will…

What You’ll Do

• be a subject matter expertise in clinical data, specifically from EHRs and HIEs, and how to apply it to solve healthcare problems.

• lead decision scientists, data engineers, and product owners to design and implement analytics solution.

• foster a team cultural of analytical excellence by balancing the pursuit of business value with innovation and continuous improvement.

• identify and translate emerging AI trends in healthcare to better address real world problems with an MVP-first mindset.

• develop, validate, implement, and support decision support tools that investigate problem spaces, identify patterns, support decision-making processes, or anticipate outcomes.

• build queries, dashboards, and data visualizations to effectively communicate analysis results and support decision making processes.

• provide thought leadership in the development of the clinical data feature store, which aims to accelerate adoption of future use cases utilizing clinical data.

• explore, validate, interpret, and summarize large amounts of data with various types/structures using advanced statistical and mathematical approaches.

• develop end-to-end analytics solutions, from developing problem statements to deployments into production.

• translate problem statements from business partners into conceptual solutions, analyze feasibility, and estimate work efforts for analytical use cases early in their lifecycle.

• create documentation of project details, like problem statements, business outcomes, data exploration, dashboard/report details, and deployment/support instructions.

• develop and participate in presentations and consultations to existing and prospective constituents on analytics opportunities, results, and solutions.

Required Qualifications

• 10+ years of relevant experience, including:

• Experience solving analytics problems in the healthcare domain using clinical data.

• Experience with HL7 FHIR and Clinical Document Architecture specifications.

• Experience with OHDSI OMOP Common Data Model.

• Experience with clinical ontologies like SNOMED, LOINC, ICD-10, RxNorm, CPT-4, HCPCS, etc..

• Experience leading analytics projects from concept to delivery by coordinating across a diverse set of stakeholders.

• Experience solving analytics problems using advanced statistics, machine learning, and mathematical algorithms.

Preferred Qualifications

• Experience using Google Cloud Platform (GCP) tools, including BigQuery, Vertex AI, and Cloud Composer to implement scalable analytics solutions.

• Experience using natural language processing (NLP), large language models (LLMs), and Generative AI (Gen AI) to extract insights from text data.

• Ability to anticipate and prevent roadblocks throughout a project lifecycle and drive resolution/mitigation.

• Proven track record of implementing cutting-edge AI solutions in a deadline driven, value oriented environment.