Senior Data Scientist – CVS Remote Jobs

Job Type: Senior Data Scientist from home
Location: Massachusetts work from home
Company: CVS Health

CVS Health’s mission is to improve people’s lives by providing innovative and high-quality health and pharmacy services that are safe, affordable, and simple to use. Every day, our team embodies this mission by pioneering bold new approaches to total health. We use large health and retail datasets, as well as advanced data science techniques, to drive the company’s pharmacy operations strategy; for example, in the last year, we have rolled out COVID-19 vaccines across the country as the leading retail provider in the country, improved the pharmacy experience for millions of patients, and optimized activities for thousands of medical providers.
We are looking for talented and passionate individuals to join this high-impact team.

Why is CVS Health Analytics and Behavior Change important?
Looking for opportunities to analyze petabytes of data using cutting-edge technologies? Do you want to generate analytical insights to improve retail and community pharmacy care?
The Analytics & Behavior Change team is an elite, rapidly growing community of nearly 1,000 MDs, PhDs, MBAs, and MScs from top-tier universities and industries who apply their clinical, technical, and economic expertise to some of today’s most pressing healthcare issues.
Join us on the cutting edge of our digital transformation. CVS Health’s combined data assets are massive and largely untapped. With unparalleled access to unique datasets, you can help us revolutionize healthcare by innovating solutions to high-visibility challenges.

What you intend to do

The Retail Operations & Immunization Analytics team provides strategic recommendations based on analytics for all pharmacy initiatives. Over the last year, this has included a large-scale rollout of COVID-19 vaccines, testing, and medications across the country, all while maximizing health equity, provider safety, and public health priorities. We are still building a strong analytics engine to optimize these ongoing initiatives and provide executive reports to internal and government leaders. Upcoming activities include the implementation of critical initiatives to optimize immunizations and pharmacy product delivery, the development of a comprehensive analytics platform across all CVS pharmacies and providers, and the enhancement of store service levels for our customers.
To improve the efficiency and effectiveness of our immunization and retail store operations, the team employs cutting-edge analytics and data science techniques. Join us as a Senior Data Scientist if you are a hands-on doer who thrives in an entrepreneurial work environment. You will manage and execute a portfolio of predictive modeling, forecasting, optimization, and evaluation projects in this role.
You will serve as an internal expert to our Retail Health business teams, assisting them in harnessing the power of data to solve mission-critical problems and develop new and innovative products. Working with a team of Data Scientists, BI developers, and analytics consultants, you will report directly to the Lead Director of Data Science for Immunization and Public Health Analytics. It is possible to be completely remote.

Responsibilities:

• Use your experience in strategy consulting and data science to successfully lead analytics and research initiatives.
• Collaborate with business partners to understand key value drivers, as well as new product challenges and goals, and their implications for public health.
• Identify opportunities to translate business requirements into data science solutions and generate actionable insights to address key challenges in healthcare and pharmacy care provision.
• Large structured and unstructured datasets from disparate enterprise databases, such as prescription drug and medical claims, EHRs, retail transaction data, and publicly available public health data sources, must be wrangled.
• Determine analytical approaches, modeling techniques, and performance metrics to optimize and evaluate new health programs or interventions – previous projects have used a diverse set of solutions using retrospective or prospective data analysis, such as classification and targeting approaches, causal inference methods, NLP and machine learning models, to optimize and evaluate new health programs or interventions.
• Create workplans, timelines, and deliverables for analytics and data science projects, and weigh business and technical tradeoffs effectively.
• Present modeling results and recommendations to senior stakeholders, tying progress to overall business goals.
• Share insights among teams to help guide collaborative efforts. Create white papers, publications, and conference presentations based on project key findings.

Pay Scale

The typical salary range for this position is: 90,000 minimum; 180,000 maximum

Please keep in mind that this range represents the average pay for all positions in the job grade in which this position is located. The actual salary offer will consider a variety of factors, including location.

Requirements:

Qualifications Required

• 2+ years of experience leading analyses and data-driven initiatives with a track record of delivering business impact and problem-solving
• Total experience of more than four years
• 2+ years of data extraction experience using SQL or Spark
• 2+ years of data analysis experience in R or Python
• Proficiency in causal inference, applied statistics, machine learning, and predictive modeling methods is required.
• Experience with data visualization and storytelling (e.g. with tools such as Tableau)

Qualifications Preferred

• Experience combining large data sets from multiple data sources and analyzing them in a big data environment using advanced analytics tools (such as ADL, Snowflake, DataRobot)
• Experience in the healthcare or public health sectors
• Working knowledge of healthcare claims data
• Ability to communicate technical concepts and implications to audiences in business, policy, and public health

Education

• A bachelor’s degree in a quantitative field such as statistics, economics, data science, or computer science is required.
• Strongly preferred: a graduate degree in a quantitative field or an MBA with a quantitative focus.