Bring your heart to CVS Health. Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric health care for a rapidly changing world. Anchored in our brand — with heart at its center — our purpose sends a personal message that how we deliver our services is just as important as what we deliver.
Our Heart At Work Behaviors support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable.
Position Summary
- Generate insights, build machine learning, deep learning and statistical predictive models and develop analytical approaches which form the foundation for driving patient engagement tactics aimed at improving medication adherence and patient experience.
- Deploy large scale machine learning and deep learning models in a production environment.
- Design and execute A/B testing, evaluate bias and develop strategies to minimize or account for experimentation bias.
- 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.)
- Write complex and efficient SQL code and leverage Exploratory Data Analysis techniques to develop insights from billions of transactional records at the Retail Pharmacy.
- Prepare communication material such as presentations and reports, collaborate effectively with business, marketing, trade and other stakeholders across the organization.
Required Qualifications
- 3+ years of hands-on experience in generating business insights, machine learning and deep learning frameworks.
- 3+ years with deployment of machine learning and deep learning models in production.
- 3+ years with cloud based ML frameworks (either AWS, Azure or GCP).
- 3+ years with Python and SQL.
- Strong proficiency with Github and MLOps.
Preferred Qualifications
- Hands-on experience working with Snowflake and Databricks.
- Experience working in healthcare or pharmaceutical industry.
Education
- Bachelor's degree or equivalent work experience in Mathematics, Statistics, Computer Science, Business Analytics, Economics, Physics, Engineering, or related discipline.
- Master's degree or PhD preferred.
Pay Range
The typical pay range for this role is: $111,240.00 - $222,480.00. This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.
In addition to your compensation, enjoy the rewards of an organization that puts our heart into caring for our colleagues and our communities. The Company offers a full range of medical, dental, and vision benefits. Eligible employees may enroll in the Company’s 401(k) retirement savings plan, and an Employee Stock Purchase Plan is also available for eligible employees. The Company provides a fully-paid term life insurance plan to eligible employees, and short-term and long-term disability benefits. CVS Health also offers numerous well-being programs, education assistance, free development courses, a CVS store discount, and discount programs with participating partners. As for time off, Company employees enjoy Paid Time Off (“PTO”) or vacation pay, as well as paid holidays throughout the calendar year. Number of paid holidays, sick time and other time off are provided consistent with relevant state law and Company policies.
For more detailed information on available benefits, please visit Benefits | CVS Health .
We anticipate the application window for this opening will close on: 10/31/2024.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
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