Cardinal Health-posted about 1 year ago
$93,500 - $133,600/Yr
Full-time • Mid Level
Phoenix, AZ
Merchant Wholesalers, Nondurable Goods

As a Full Stack Data Scientist at Cardinal Health's AI Center of Excellence, you will be instrumental in leveraging technology to enhance healthcare solutions. This role involves collaborating with business stakeholders to develop data-driven applications, building machine learning models, and creating user-friendly interfaces. You will bridge the gap between machine learning and front-end development, ensuring seamless integration of innovative solutions into existing systems.

  • Develop intuitive and user-friendly web applications using modern front-end frameworks (e.g., React, Angular, Vue.js) to showcase and interact with ML/GenAI solutions.
  • Design, train, and optimize machine learning models for various applications like forecasting and classification.
  • Explore and implement Generative AI technologies to enhance applications or create new solutions.
  • Design and implement RESTful APIs to integrate ML models or GenAI solutions with other systems.
  • Design, develop, and maintain robust and scalable ML pipelines, including data ingestion and model training.
  • Ensure scalability and performance of ML and GenAI applications with large data volumes.
  • Develop interactive visualizations to communicate data analysis results to stakeholders.
  • Collaborate with cross-functional teams to ensure successful project delivery.
  • Stay current on the latest trends in AI and experiment with new technologies.
  • Bachelor's degree in mathematics, Statistics, Engineering, Computer Science, or equivalent work experience.
  • At least 4 years of experience as a Full Stack Machine Learning Engineer or similar role.
  • Proficiency in HTML, HTML5, CSS3, JavaScript (React preferred), Angular, Vue.js, Python, Java, Node.js, Flask/Django, FastAPI, PostgreSQL.
  • Experience with popular React libraries and tools (e.g., Redux, React Router).
  • Experience in DevOps tools like Docker, Kubernetes, Airflow; version control using Git and CI/CD pipelines.
  • Knowledge of clinical domain and datasets.
  • Experience in Generative AI, RAG implementation, and Large Language Models (LLMs).
  • Experience with Machine Learning technologies such as Jupyter Notebooks, NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch.
  • Understanding of cloud data engineering concepts including GCP, Vertex AI, Cloud functions.
  • 2+ years in the Healthcare industry and knowledge of clinical data.
  • Delivery experience with Google Cloud Platform.
  • Agile development skills and experience.
  • Experience designing and developing machine learning and deep learning solutions.
  • Medical, dental and vision coverage
  • Paid time off plan
  • Health savings account (HSA)
  • 401k savings plan
  • Access to wages before pay day with myFlexPay
  • Flexible spending accounts (FSAs)
  • Short- and long-term disability coverage
  • Work-Life resources
  • Paid parental leave
  • Healthy lifestyle programs
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