Data Scientist

CVS Health

Remote

Quick summary

Work type: Remote
Location: New York, NY
Posted: 6 days ago
Closes: Jul 6, 2026
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $156k

$87k most similar roles pay here $213k

This listing doesn't post a salary. Most similar roles pay $126,800–$185,650.

Based on 240 similar postings.

Employer

About CVS Health

CVS Health is a leading American healthcare company operating retail pharmacies, pharmacy benefit management services, and a health insurance segment through Aetna, one of the nation''s largest health insurers. Industry: Healthcare & Pharmacy

CVS Health currently has 409 open roles on FindRole.

Listed pay typically runs $118,450–$284,280 across 135 roles with salary data.

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At a glance

TL;DR · Data Scientist

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Aetna Resources, LLC, a CVS Health company, seeks a Data Scientist in New York to support large-scale data initiatives and product management within a matrixed organization. This role involves developing data science products through the end-to-end lifecycle workflow, including feature engineering, model training, and hyperparameter tuning. The ideal candidate will have experience with machine learning algorithms, predictive modeling, and statistical analysis using tools like Scikit-Learn, SpaCy, PyTorch, Spark NLP, R, Python, MySQL, and GCP. They should be proficient in ETL processes, CI/CD pipelines, and contributing to large-scale applications development projects in the healthcare sector.

Skills

Python R SQL Google Cloud Platform CI/CD Scikit-Learn SpaCy PyTorch Spark NLP MySQL ETL Machine Learning NLP Predictive Modeling Statistical Analysis Feature Engineering Distributed Model Training Relational Database Concepts

What you'll do

Develop and apply machine learning algorithms for predictive modeling in healthcare data.
Design and implement ETL processes for large datasets in the healthcare sector.
Conduct quantitative analysis using clustering, regression, and pattern recognition techniques.
Engineer features and train models for both supervised and unsupervised learning tasks.
Support product management and technology modernization initiatives within a matrixed organization.
Contribute to end-to-end data science lifecycle workflows from model training to deployment.

What we're looking for

Master’s degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Analytics, or related field required.
At least two years of experience supporting large data and technology modernization initiatives.
Experience with end-to-end data science lifecycle workflow including model training and hyperparameter tuning.
Proficiency in machine learning algorithms, predictive modeling, and statistical analysis using R, Python, MySQL, SQL.
Expertise in Google Cloud Platform (GCP) and CI/CD processes for application deployment.
Strong background in designing data models and solutions for analytical and reporting use cases.

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