Data/Machine Learning Scientist

Headquartered in Dublin, Ohio, Cardinal Health, Inc. (NYSE: CAH) is a global, integrated healthcare services and products company connecting patients, providers, payers, pharmacists and manufacturers for integrated care coordination and better patient management. Backed by nearly 100 years of experience, with more than 50,000 employees in nearly 60 countries, Cardinal Health ranks among the top 20 on the Fortune 500.

Department Overview:

AI & Data Science team builds analytics and artificial intelligence solutions that drive success for Cardinal Health by creating material savings, efficiencies and revenue growth opportunities. The team drives business innovation by leveraging emerging technologies and turning them into differentiating business capabilities.

Job Overview:

Responsibilities:

- As Data scientist will assess business opportunities and promote use of data science, analytics within domain and build internal and external resources and expertise.

- The role requires being hands-on and working together with external and internal partners to develop, test and operationalize data science and analytical solutions as well as ensure its adoption by businesses.

- Work to leverage data (Transactional / Big Data, External/ Internal Data, Structured/ Unstructured Data) and analytics methods to develop analytics solutions.

Qualifications:

- 6 - 8 years of experience, preferred.

- BTech-BE from Tier 1/2 engineering schools or MStat/MS (Math)/MA Econ/ MS Analytics/data science from Tier 1/2 schools.

- Knowledge on CI/CD method of working and MLOps.

- Lead/Ideate Agentic AI, GenAI and Classic ML initiative in AICoE.

- Design ML/LLM pipelines, good knowledge of RAG, prompt engineering.

- Monitor system performance, logs, retrieval quality and prompt-effectiveness.

- Design, develop, and maintain robust and scalable cloud functions using Python, FastAPI or Flask, and SQLModel/SQLAlchemy.

- Integrate microservices with ApigeeX for API management, security (authentication, authorization, rate limiting), monitoring, and analytics.

- Excellent Programming/ Data Wrangling skills with some languages like Python, R, Scala, Java, SQL.

- Skills in areas like Agentic AI, GenAI, and some other traditional AI techniques like optimization, Statistics, Machine learning, NLP, Image/ Video, Speech analytics.

- Good knowledge of some of the analytical platforms like GCP, Big Query, Google Cloud Storage, MS Azure, Google Looker, Databricks etc.