Data Scientist

About this role

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Skills you'll use

What you'll do

• 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

Who can apply

• 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.

About Cardinal Health

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