Senior Full Stack Data Scientist

Sr. Data Scientist Job Description

At Cardinal Health's Artificial Intelligence Center of Excellence (AI CoE), we are pushing the boundaries of healthcare with cutting-edge Data Science and Artificial Intelligence (AI). Our mission is to leverage the power of data to create innovative solutions that improve patient outcomes, streamline operations, and enhance the overall healthcare experience.

We are seeking a highly motivated and experienced Senior Data Scientist to join our team as a thought leader and architect of our AI strategy. You will play a critical role in fulfilling our vision through delivery of impactful solutions that drive real-world change.

Why Join Cardinal Health's AI CoE?

• Make a Real Difference: Contribute to cutting-edge solutions that improve patient care, enhance healthcare operations, and drive positive change in the industry.
• Work with a Passionate Team: Join a team of highly skilled data scientists who are committed to pushing the boundaries of AI in healthcare.
• Grow and Develop: Access opportunities for professional growth, mentorship, and development within a dynamic and innovative environment

Responsibilities:

• Lead the Development of Innovative AI solutions: You will be responsible for designing, implementing, and scaling sophisticated AI solutions that address key business challenges within the healthcare industry. This will involve leveraging your expertise in areas such as:
  • Machine Learning (ML): Developing advanced ML models for forecasting, classification, risk prediction, and other critical applications.
  • Generative AI: Exploring and leveraging the latest Generative AI (GenAI) technologies, including Large Language Models (LLMs), for applications like summarization, generation, classification and extraction.
  • RAG Technologies: Building robust Retrieval Augmented Generation (RAG) systems to integrate LLMs with vast repositories of healthcare and business data, ensuring accurate and relevant outputs.
• Shape Our AI Strategy: You will work closely with key stakeholders across the organization to understand their needs and translate them into actionable AI-driven or AI-powered solutions. You will be a champion for AI within Cardinal Health, influencing the direction of our technology roadmap and ensuring alignment with our overall business objectives.
• Guide and Mentor a Team of Data Scientists and ML Engineer: You will provide technical guidance, mentorship, and support to a team of skilled geographically distributed data scientists, fostering a collaborative and innovative environment that encourages continuous learning and growth.
• Embrace a AI-Driven Culture: You will foster a culture of data-driven decision-making, promoting the use of AI insights to drive business outcomes and improve customer experience and patient care.

Qualifications:

• 8-12 years of experience, preferred
• Bachelor's degree in computer science or related field, or equivalent work experience, preferred
• Proven AI/ML Expertise: Minimum of 4 years of experience in data science, with a strong track record of success in developing and deploying complex AI/ML solutions.
• GenAI Proficiency: Deep understanding of Generative AI concepts, including LLMs, RAG technologies, embedding models, prompting techniques, and vector databases.
• Healthcare Data Acumen: Extensive knowledge of healthcare data, including clinical data, patient demographics, and claims data. Understanding of HIPAA and other relevant regulations, preferred.
• Cloud Computing Expertise: Experience working with cloud platforms like Google Cloud Platform (GCP), Azure, or AWS for data processing, model training, evaluation, monitoring, deployment and support.
• Leadership and Communication: Proven ability to lead data science projects, mentor colleagues, and effectively communicate complex technical concepts to both technical and non-technical audiences.
• Strong Technical Skills: Proficiency in Python, statistical programming languages, machine learning libraries (Scikit-learn, TensorFlow, PyTorch), cloud platforms, and data engineering tools.
• CI/CD Automation: Experience in building and implementing CI/CD pipelines for ML models and other solutions, ensuring seamless integration and deployment in production environments.
• REST API Development: Familiarity with RESTful API design and implementation, including building robust APIs to integrate your ML models and GenAI solutions with existing systems.
• Software Engineering Best Practices: Working understanding of software engineering patterns, solutions architecture, information architecture,