Senior 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 $159k

$96k most similar roles pay here $220k

This listing doesn't post a salary. Most similar roles pay $126,800–$191,371.

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 · Senior Data Scientist

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Caremark LLC, a CVS Health company, is seeking a Senior Data Scientist in New York to develop and apply advanced mathematical and computational models for data extraction and manipulation. This role involves working with big data platforms like Hadoop, Spark, and Airflow to translate complex analytical problems into efficient programs using PySpark, Scala, or PL/SQL. The ideal candidate will have expertise in machine learning frameworks such as Scikit-Learn and PyTorch, along with experience in marketing analytics, clinical trials, and health research. Key responsibilities include feature engineering, model training, hyperparameter tuning, and implementing supervised and unsupervised learning techniques to solve real-world business problems at scale.

Skills

Python R SQL Hadoop Spark Airflow Kafka PySpark Scala PL/SQL Teradata BTEQ Scikit-Learn Spacy Pytorch Spark NLP Marketing analytics Clinical trials Health research Containerized services Docker CI/CD Machine Learning NLP Feature engineering Model training Hyperparameter tuning Clustering Regression Pattern recognition

What you'll do

Develop mathematical models for data extraction and manipulation using R, Python, or SQL.
Implement machine learning algorithms with frameworks like Scikit-Learn, PyTorch, or Spark NLP.
Translate complex analytical problems into efficient programs using PySpark, Scala, PL/SQL, or Teradata BTEQ.
Manage big data platforms such as Hadoop, Spark, and NoSQL databases for large-scale analytics.
Conduct qualitative analysis employing techniques like clustering, regression, and pattern recognition.
Feature engineering and model training for supervised and unsupervised learning tasks.

What we're looking for

Master’s degree in Computer Science, Data Science, or related field required.
2 years of experience with R, Python, SQL.
Expertise in big data platforms like Hadoop, Spark, Kafka, NoSQL.
Experience translating analytical problems into structured programs using PySpark, Scala.
Proficiency in machine learning and NLP tools such as Scikit-Learn, SpaCy, PyTorch.
Knowledge of marketing analytics or health research applications.
Skills in containerized services management and model training techniques.

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