Data 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

The primary role of the Data Scientist is to support, maintain, and iteratively improve production Agentic AI and Machine Learning models within the Finance Digital Solutions ecosystem. This position focuses on the execution, monitoring, and optimization of Generative AI agents, prompt templates, and core data science pipelines. The candidate will utilize deep understanding of model behavior, agent observability, and statistical validation to ensure high-quality and reliable outputs in production finance environments.

Responsibilities

• Monitor and evaluate the outputs of production Agentic AI models, verifying performance metrics and maintaining agent evaluation data.
• Design, test, and optimize prompt engineering strategies to improve model response accuracy, latency, and relevance.
• Perform exploratory data analysis and build transformation pipelines using Python and SQL to support ongoing model performance.
• Support API frameworks such as FastAPI or Flask that serve model predictions and agent decisions to upstream finance systems.
• Collaborate with MLOps and Run Lead to troubleshoot model drift, logic errors, or connection issues to underlying databases.
• Develop an understanding of complex financial business processes (such as SAP, Salesforce, and Postgres tables) to ensure model logic matches business requirements.
• Produce and analyze insights from key performance indicators of models, proposing updates and modifications where necessary.
• 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
  
  

• 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
• Direct experience with Prompt Engineering, Agent Engines, Agent Evaluation, and Agent Observation frameworks.
• Experience with GCP Cloud Platform, including GCP Cloud Functions and BigQuery.
• Familiarity with enterprise applications such as SAP and Salesforce is highly preferred.
• Excellent communication and collaboration skills to bridge technical models with operational financial goals.
• 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.
• 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
• Preferably good knowledge of Agile & SCRUM development processes
  
  

• Excellent communication and storytelling skills (oral, written and presentation)
• Highly driven, energetic, flexible & ability to multitask
• Ability to work with teams/ stakeholders to drive change/ adoption of analytics solutions