Cognizant is a global leader in digital, technology, consulting and operations services. With a presence in over 40 countries, the company helps enterprises across industries transform their business models using AI, cloud, and analytics. Cognizant’s AI Builder practice focuses on turning AI investments into measurable business value, delivering end‑to‑end solutions that blend deep industry knowledge with cutting‑edge technology. The organization promotes a culture of continuous learning, diversity, and social responsibility, encouraging employees to innovate responsibly and contribute to sustainable outcomes. The Data Analyst role is a hybrid, day‑shift position that sits at the intersection of data engineering, analytics, and generative AI. Reporting to the Analytics Lead, the analyst will design, build, and maintain Python‑based data pipelines, embed responsible AI practices, and create LangChain and LangGraph workflows that enable automated insight generation. The role demands a strong grasp of large language model fundamentals, prompt engineering, and the ability to translate complex data into actionable business recommendations while adhering to governance standards. Key Responsibilities: 1. Collect, clean, and structure large enterprise data sets using Python, ensuring data quality for reporting and forecasting. 2. Design reusable, scalable data pipelines that handle ingestion, transformation, and validation. 3. Build generative AI workflows that leverage LLMs for text summarization, knowledge extraction, and automated reporting. 4. Implement model‑context protocol integrations to manage prompts, context windows, and tool connections reliably. 5. Develop and maintain LangGraph workflows that orchestrate multi‑step AI processes with clear graph structures. 6. Create LangChain agents that securely connect language models to internal data sources for advanced querying. 7. Perform exploratory analysis on structured and unstructured data to surface trends, anomalies, and growth opportunities. 8. Collaborate with product, engineering, and operations teams to define analytical requirements and align deliverables with strategic goals. 9. Establish data quality checks, performance metrics, and comprehensive documentation for all solutions. 10. Mentor junior analysts on Python best practices, prompt design, model evaluation, and data storytelling. Tech Stack: Python (Pandas, NumPy, PyTest), SQL, Git, Docker, LangChain, LangGraph, Large Language Models (e.g., GPT‑4), Azure/AWS cloud services, Tableau/PowerBI for visualization. Growth Path: Analysts can progress to Senior Analyst, Analytics Consultant, AI Solutions Architect, or Product Manager roles, with opportunities to lead cross‑functional AI projects and contribute to Cognizant’s AI research initiatives. Why Join Cognizant? The company offers exposure to world‑class AI platforms, a collaborative hybrid work environment, robust learning programs, and a commitment to ethical AI. Employees benefit from mentorship, global mobility, and a clear career ladder that rewards technical expertise and business impact.