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Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable.

Position Summary

As a Lead Data Scientist on the Retail Strategic Health Analytics team, you will play a critical role on some of the most impactful projects supporting the Retail Pharmacy at CVS. Our work broadly involves improving pharmacy staffing outcomes, leveraging a variety of techniques, including but not limited, to time series modeling, unsupervised learning, causal inference, and stochastic simulation. You will be expected to serve as a thought leader, mentor, and developer of advanced AI/ML solutions.

• Develop, validate, and execute AI/ML models to solve complex business problems.
• Collaborate with senior leadership and subject matter experts to outline requirements and areas for support
• Evaluate and blueprint solutions using AI/ML in conjunction with data scientists and team leadership
• Coordinate with MLOps and Data Engineers to streamline data and ML/AI pipelines for deployment
• Outline and execute on methods to fine-tune models for performance and accuracy.
• Contribute to team eminence for AI/ML methods and coding and documentation standards.
• Serve as a mentor to junior data scientists, providing guidance on methods and resources, and reviewing analytical solutions.
• Compile and present results to executive audiences in a clear, compelling, and honest manner.

• 1+ years of experience with building Time Series models and pipelines related to demand forecasting
• 5+ years of experience developing proven AI-driven applications
• 5+ years of experience using machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and natural language processing and generative AI techniques with proven track record of end-to-end building and deploying advanced applications, including knowledge of model serialization and deserialization.
• 5+ years of experience with data preprocessing, feature engineering, and model evaluation
• 5+ years of experience and proficiency in working with large datasets and distributed computing platforms
• 1+ years of experience with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for deploying AI solutions

• Healthcare Industry experience is desired.
• Knowledge of data privacy and security considerations in AI development.
• Expertise in generative AI techniques, including generative adversarial networks (GANs), variational autoencoders (VAEs), or similar architectures.
• Proficiency in integrating low-code and no-code solutions with custom code and external systems through APIs and connectors.
• Familiarity with causal inference methods and counterfactual reasoning in machine learning.
• Knowledge of Bayesian machine learning and probabilistic programming frameworks.
• Proficiency in deploying ML models in production environments, including containerization, and serving frameworks.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• PhD or Master's in Artificial Intelligence, Engineering or a related field.