CVS Health

Lead Data Scientist – Clinical Product Analytics & Behavior Change

CVS Health

full-time

Posted on:

Origin:  • 🇺🇸 United States • Illinois, New York

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Salary

💰 $106,605 - $284,280 per year

Job Level

Senior

Tech Stack

AWSCloudPythonSQL

About the role

  • Be the technical product owner of our medication adherence solution, responsible for developing a product roadmap, managing and improving product performance, and designing impactful member experiences and nudges that enable members to stay adherent to their medication regimen.
  • Mentor and lead a multi-disciplinary team of data scientists and engineers that develops and deploys robust machine learning and statistical models to optimize patient engagement tactics, patient experience, and medication adherence.
  • 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.
  • 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, 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.

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
  • 7+ years work experience (inclusive of applied research experience)
  • Strong theoretical and hands-on experience with statistics and machine learning in general
  • Strong programming skills in Python, R and SQL
  • Hands-on experience with cloud computing (Google Cloud, AWS, etc.)
  • Hands-on experience with tools and processes for version control (i.e. git, GitHub)