Data Analyst

Round 1: Online aptitude & coding test → Round 2: Technical interview (Python, AI concepts, problem solving) → Round 3: HR interview (fit, motivations, compensation)

Cognant fosters a collaborative environment where continuous learning and innovation are encouraged. Employees enjoy a blend of on‑site and remote work, robust mentorship programs, and clear pathways for career growth, all while maintaining a healthy work‑life balance.

Cognizant's interview process typically starts with an online aptitude and coding test, followed by a technical interview focusing on Python, data pipelines, and AI concepts. The final HR round assesses cultural fit and communication skills. Candidates report a moderate difficulty level and recommend practicing data‑centric coding problems and reviewing generative AI fundamentals.

Bachelor's or Master's degree in Computer Science, Information Technology, Electronics, Statistics or related fields; minimum 60% aggregate (or CGPA 6.0/10); batch years 2022‑2026 acceptable; maximum 2 backlogs allowed; strong communication skills; eligibility to work in India.

Cognizant is a global leader in digital, technology, consulting and operations services. With a presence in over 40 countries, the company helps enterprises transform their business models through AI‑driven solutions, cloud migration, and data‑centric strategies. Cognizant’s AI Builder practice focuses on turning AI investments into measurable business value, leveraging deep industry expertise and cutting‑edge research. The firm’s culture emphasizes continuous learning, diversity, and sustainability, making it a preferred destination for technology professionals who want to work on large‑scale, impact‑driven projects. The Data Analyst role in Chennai is a hybrid day‑shift position that sits at the intersection of data engineering, analytics, and generative AI. The analyst will be responsible for designing end‑to‑end data pipelines, building AI‑enabled workflows, and delivering actionable insights that support strategic decision‑making across the enterprise. This position demands strong Python expertise, hands‑on experience with large language models, and the ability to orchestrate complex graph‑based processes using LangGraph and LangChain. Key Responsibilities: 1. Collect, clean, and structure complex enterprise data sets using Python to enable accurate reporting and forecasting. 2. Design and implement scalable data pipelines and reusable code components for ingestion, transformation, and validation. 3. Build generative AI workflows that automate text analysis, summarization, and knowledge extraction while adhering to governance standards. 4. Develop model‑context protocol integrations to manage prompts, context windows, and tool connections reliably. 5. Construct and maintain LangGraph workflows that organize multi‑step analytical and generative AI processes into transparent graph structures. 6. Create LangChain‑based agents that securely connect language models with internal data sources for advanced querying and reasoning. 7. Analyze large structured and unstructured data sets to uncover trends, anomalies, and opportunities, translating findings into concise recommendations. 8. Collaborate with product, engineering, and business operations teams to define analytical requirements and align outputs with strategic goals. 9. Establish rigorous data quality checks, performance metrics, and documentation for all Python and AI solutions. 10. Mentor junior analysts on best practices in Python coding, prompt design, model evaluation, and data storytelling. Tech Stack: Python (pandas, NumPy, PyTest), SQL, LangChain, LangGraph, Large Language Models (e.g., GPT‑4, Claude), REST APIs, Docker, Git, cloud platforms (Azure/AWS). Growth Path: Analysts can progress to Senior Analyst, Lead Analyst, AI Solutions Architect, or Manager – Innovation, with opportunities to lead cross‑functional AI projects and contribute to Cognizant’s AI research initiatives. Why Join Cognizant: The company offers a robust learning ecosystem, sponsorship for certifications, exposure to global clients, and a culture that values sustainability and responsible AI. Employees benefit from flexible hybrid work, competitive compensation, and a clear roadmap for career advancement.