Data Analyst

Cognizant is hiring a Data Analyst in Chennai to build Python data pipelines and generative AI workflows using LLMs, LangGraph, LangChain, and Model Context Protocol. The listing targets experienced candidates, so freshers should apply only with strong demonstrable AI project work.

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Technical

1. How do you handle missing or dirty data using Python pandas before feeding it into a data pipeline?
2. Can you explain how you would set up a LangChain chain or agent to retrieve internal data securely?
3. What are the key differences between using LangGraph and standard LangChain for multi-step LLM workflows?

Scenario

1. What would you do if an LLM workflow you deployed starts returning hallucinated or inconsistent summaries for enterprise text data?
2. How would you troubleshoot a Python data pipeline that has suddenly slowed down significantly during ingestion?

HR

1. Why do you want to work in a hybrid analytics role focused on generative AI at Cognizant?
2. How do you keep your technical skills updated given how rapidly generative AI frameworks change?

About Cognizant

1. How does Cognizant leverage generative AI solutions to drive digital transformation for its enterprise clients?

Practice questions written from the job listing, not this company's real interview questions.

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