Senior Data Scientist - Forecasting and AI Development

CVS Health

Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$111,240–$222,480 / yr
Posted
2 days ago
Closes
Jul 5, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $164k
This role $167k
$98k most similar roles pay here $236k

This role pays more than 55% of similar roles. Most pay $127,790–$200,862 — the shaded band above. At the midpoint, this role pays about $167k versus about $164k for comparable roles.

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 135 open roles on FindRole.

Listed pay typically runs $118,450–$284,280 across 132 roles with salary data.

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At a glance

TL;DR · Senior Data Scientist - Forecasting and AI Development

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As a Senior Data Scientist in the Forecasting Center of Excellence, you will lead the development and enhancement of critical forecasting tools using advanced statistical and machine learning techniques. Your daily tasks include refining time series models, implementing ensemble methods, and integrating AI-driven approaches to improve accuracy and scalability. You will work with Python libraries such as pandas, NumPy, scikit-learn, and statsmodels to develop sophisticated forecasting solutions that address complex business challenges in labor and financial planning. Ideal candidates have a strong background in hierarchical forecasting, feature engineering, and MLOps practices, along with experience in deep learning techniques like LSTM and transformers. This role requires excellent problem-solving skills and the ability to communicate effectively with stakeholders across various departments.

Skills

Python pandas NumPy scikit-learn statsmodels time series forecasting ensemble modeling hierarchical forecasting AI/ML techniques feature engineering exploratory data analysis MLOps LSTM transformers optimization techniques

What you'll do

  • Develop and refine time series forecasting models using statistical and machine learning techniques.
  • Implement ensemble modeling strategies to enhance forecast accuracy and robustness.
  • Conduct exploratory data analysis and feature engineering for AI-driven forecasting workflows.
  • Evaluate and optimize hierarchical or multi-level forecasting systems for scalability.
  • Apply deep learning approaches, such as LSTM and transformers, to time series data.
  • Collaborate on MLOps practices for model deployment, monitoring, and maintenance.

What we're looking for

  • Over 3 years of experience in data science or related quantitative field.
  • Expertise in time series forecasting, including statistical and machine learning methods.
  • Experience with ensemble modeling techniques and hierarchical forecasting.
  • Proficient in Python for data analysis and model development (pandas, scikit-learn).
  • Applied AI/ML techniques to feature engineering and exploratory data analysis.
  • Strong problem-solving skills and ability to communicate effectively with stakeholders.

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