We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.

Position Summary:

We seek a Senior Data Scientist to join our Medicare Member Experience data science team. You will design and deploy agent-based solutions, including Model Context Protocol (MCP) servers, on Google Cloud Platform (GCP) to improve our Medicare Stars program. These agents will extract information from unstructured data using a mix of local and cloud-hosted large language models (LLMs).

 

Key responsibilities:

• Design, build, and deploy MCP and agent-based solutions on GCP
• Develop NLP-driven information extraction pipelines
• Build reliable agent pipelines, from input handling to validated outputs
• Evaluate and monitor agent performance in production
• Partner with engineers, domain experts, and stakeholders to deliver production systems

 

Required Qualifications:

• 3+ years coding Python in a production cloud environment
• 3+ years developing and testing NLP models using PyTorch and Transformers
• Experience deploying LLM-based systems to production with CI/CD
• Experience with agent evaluation and guardrails
• Experience with GPU-mounted containers for development and inference
• Proficiency in SQL and Git
• Strong analytic and communication skills across technical and business audiences

 

Preferred Qualifications:

• 3+ years using GCP services such as BigQuery, Kubernetes, Vertex AI, and GKE
• Experience building MCP servers
• Experience with agent frameworks such as LangGraph, LangChain, OpenAI Agents SDK, or ADK
• Experience with LLMOps and MLOps, including monitoring, versioning, and data and model provenance
• Experience deploying local LLMs with vLLM or SGLang
• Experience with CUDA, TensorRT, and TensorRT-LLM for GPU inference optimization
• Experience fine-tuning encoder, decoder, and encoder-decoder models
• Experience hardening container images, including distroless patterns and CVE scanning
• Experience leading AI projects end to end and mentoring junior colleagues
• Advanced degree in data science, statistics, CS, engineering, or a related field

Education:

• Bachelor's degree in data science, statistics, CS, engineering, or a related field

Anticipated Weekly Hours

40

Time Type

Full time

Pay Range

The typical pay range for this role is:

$92,700.00 - $203,940.00

This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls.  The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors.  This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. 
 

Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.

Great benefits for great people

We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.

This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.

Additional details about available benefits are provided during the application process and on Benefits Moments.

We anticipate the application window for this opening will close on: 11/21/2026

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.