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# Sr. Data Scientist

- **Company:** CVS Health
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Salary:** $111,240.0 - $222,480.0
- **Contract:** Internship / Graduate position
- **Skills:** Algorithm Design, Data Analysis, Big Data, Computer Programming, Data Mining, Data Systems, Data Visualization, Apache Hadoop, Python (Programming Language), Machine Learning, Natural Language Processing, Power BI, DataOps, SAS (Software), SQL Databases, Tableau (Software), Information Technology, Programming Languages
- **Published:** June 22, 2026
- **Apply:** https://dejobs.org/x/x/DD3AC3FD634E4B209C6D59A281F1232E/job/

## About the Role

Requirements: Master's degree (or foreign equivalent) in Computer Science, Data Science, Statistics, Mathematics, Analytics, Biostatistics, Public Health, or a related field and completion of a university- level course, research project, internship, or thesis in each of the following: Analyzing large data sets from multiple data sources; Data analysis for health care industry, products, or systems; Marketing analytics, clinical trials, or health research; Analytics experience within the retail and/or healthcare industries; Machine learning, statistical analysis, and predictive modeling; Programming in R, Hadoop, or Python; SAS or SQL programming languages; and Visualization tools, including PowerBI or Tableau.

## Description

Position Summary: Aetna Resources LLC, a CVS Health company, is hiring for the following role in New York, NY: Sr. Data Scientist to develop and implement analytics applications and models to transform data into meaningful information. Duties include: design and develop data solutions using industry leading tools, technologies and best practices to profile data and develop efficient ingestion by sourcing data from PBM, Specialty, Retail, and/or HealthCare business; develop advanced algorithms and statistical predictive models to evaluate scenarios, predict outcomes, and provide usable information on health metrics and potential future outcomes; utilize data mining, data modeling, natural language processing, and machine learning to extract and manipulate data from multiple large data sources and deliver predictive models that inform solutions for in-house teams (i.e. pharmacy pricing, medical costs, risk scores, onboarding) and customer engagement across critical journeys (i.e. calories,
heart rate, breast cancer, maternity); utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data in various forms and solve complex business problems; visualize and interpret data and create reports, manipulate data using statistical software, and compare models using statistical performance metrics; and support deployment of insights across multiple channels using analysis methods, machine learning, and statistical analyses. Telecommuting available. Multiple positions.


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