Lead Data Scientist

6 days ago

New York, New York, United States CVS Health Full time
Job Summary

CVS Health is seeking a highly skilled Lead Data Scientist to join our Retail Strategic Health Analytics team. As a key member of our team, you will play a critical role in developing and executing AI/ML models to solve complex business problems in the retail pharmacy space.

Key Responsibilities
  • Develop and validate AI/ML models to improve pharmacy staffing outcomes and drive business growth.
  • 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.
Requirements
  • 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 a proven track record of end-to-end building and deploying advanced applications.
  • 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 building Time Series models and pipelines related to demand forecasting.
  • 1+ years of experience with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for deploying AI solutions.
Preferred Qualifications
  • 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.
Education
  • 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.

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