Job Title: Senior Data Scientist - ML/AI Digital Workplace Experience

Job Location: Work at Home, Massachusetts, United States

Job Location Type: Remote

Job Contract Type: Full time

Job Seniority Level:

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 are seeking a highly skilled Senior Data Scientist to join our ML Digital Experience & Digital Workplace team. In this role, you will lead the design, development, and deployment of advanced machine learning models and Generative AI (GenAI) solutions that transform the digital workplace experience. You will work at the intersection of data science, AI innovation, and enterprise technology to deliver intelligent products and capabilities that drive productivity, automation, and enhanced user experiences across the organization. This is an opportunity to shape the future of how employees interact with digital tools and platforms by leveraging cutting-edge ML and GenAI technologies to solve complex business challenges at scale.

Key Responsibilities

Machine Learning & AI Development: Design, build, and deploy production-grade ML models with end-to-end pipelines and MLOps best practices to ensure scalability, reproducibility, and continuous improvement.
Generative AI & LLMs: Lead the design and deployment of GenAI solutions leveraging LLMs, RAG, prompt engineering, and fine-tuning to build intelligent assistants, conversational agents, and knowledge retrieval tools.
Data Analysis & Insights: Analyze large-scale datasets using statistical methods and advanced analytical frameworks to uncover actionable patterns and measure AI/ML impact.
Digital Workplace & Employee Experience: Partner cross-functionally to deliver high-impact AI/ML use cases—including predictive analytics, anomaly detection, and workflow automation—across enterprise digital workplace platforms.
Collaboration, Technical Leadership & AI Governance: Serve as a subject matter expert in ML and GenAI, mentoring team members, driving actionable business recommendations, and contributing to responsible AI governance frameworks.

Required Qualifications

5+ years of hands-on experience delivering production-level ML/AI solutions with strong expertise in Generative AI, LLMs, RAG architectures, and prompt engineering.
Advanced proficiency in Python, ML/AI frameworks (scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain), NLP techniques, SQL, and large-scale data platforms (Databricks, Spark, BigQuery).
Hands-on experience with MLOps practices (model versioning, CI/CD, experiment tracking, monitoring) and cloud platforms (Azure, AWS, GCP) and their AI/ML services.
Strong foundation in statistics, probability, and experimental design with the ability to apply rigorous analytical methods to real-world problems.
Excellent storytelling and communication skills with the ability to convey complex technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications

Master's degree or Ph.D. in Data Science, Computer Science, Machine Learning, Statistics, Mathematics, Computational Linguistics, or a related quantitative field.
Experience with vector databases (Pinecone, Weaviate, FAISS), AI orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel), and enterprise AI platforms such as Azure OpenAI Service or Azure Machine Learning.
Knowledge of digital workplace technologies (Microsoft 365, ServiceNow, endpoint management) with experience in enterprise telemetry and application usage analytics.
Familiarity with responsible AI principles and explainability techniques (SHAP, LIME), with experience building real-time inference systems and deploying models via APIs and microservices.
Experience with computer vision or multi-modal AI, prior work in healthcare or enterprise IT environments, and relevant cloud AI/ML certifications (Azure AI Engineer, AWS ML Specialty, Google Professional ML Engineer).

Education

Bachelor’s degree in Data Science, Computer Science, Machine Learning, Statistics, Mathematics, Computational Linguistics, or a related quantitative field.

Job Seniority Level:

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