WNS, part of Capgemini, is an Agentic AI-powered leader in intelligent operations and transformation, serving more than 700 clients across 10 industries, including Banking and Financial Services, Healthcare, Insurance, Shipping and Logistics, and Travel and Hospitality. We bring together deep domain excellence – WNS’ core differentiator – with AI-powered platforms and analytics to help businesses innovate, scale, adapt and build resilience in a world defined by disruption.Our purpose is clear: to enable lasting business value by designing intelligent, human-led solutions that deliver sustainable outcomes and a differentiated impact. With three global headquarters across four continents, operations in 13 countries, 65 delivery centers and more than 66,000 employees, WNS combines scale, expertise and execution to create meaningful, measurable impact.

Lead Associate – Data Scientist & AI Engineer (2+ Years Experience)LocationHybrid / Remote (as per project requirement)About the RoleWe are seeking a highly skilled Data Scientist & AI Engineer with 4+ years of experience in retail data science, campaign measurement, and Generative AI systems. The role involves designing and deploying applied AI solutions, leading media insights initiatives, and building scalable generative AI workflows. This position is ideal for professionals who thrive at the intersection of applied data science and AI engineering, with exposure to Forward Deployed Engineering (FDE) responsibilities.Key ResponsibilitiesGenerative AI & LLM EngineeringArchitect and implement RAG systems, LangChain/LangGraph pipelines, and multi-agent frameworks.Optimize prompts, embeddings, and semantic search relevance.Deploy and monitor LLM-enabled workflows using CrewAI, MCP Servers, Gemini API, Claude Code, Codex, and Cursor.Data Science & MeasurementConduct causal inference, uplift modeling, and incrementality testing.Design attribution models and measure ROAS for retail campaigns.Segment audiences and deliver actionable insights for marketing effectiveness.Visualization & BIBuild dashboards and reports using Power BI, DAX, Python, and SQL.Communicate insights through advanced visualization techniques.Data Engineering & CloudDevelop scalable data pipelines on Azure Databricks, Snowflake, and ADF.Implement ETL/ELT workflows, Blob Storage integrations, and REST API automation.Manage CI/CD workflows using GitHub and ADBFS.Project & OperationsLead cross-functional teams and mentor junior analysts.Manage SLAs, incident reports, and RCA documentation.Collaborate with clients and stakeholders to deliver measurable outcomes.SkillsetMandatory SkillsGenerative AI & LLM Engineering (RAG, LangChain, LangGraph, CrewAI, Agentic AI, MCP Servers, Gemini API, Vector Embeddings, Prompt Engineering, Multi-Agent Systems)Data Science & Measurement (Causal Inference, Uplift Modeling, Attribution, ROAS Measurement)Python (Advanced), PySpark, SQL, Power BI, DAXAzure Databricks, Snowflake, ADF, Blob StorageGitHub CI/CD, REST APIs, ETL/ELT AutomationStrong communication and client-facing skillsBehavioral SkillsAnalytical and problem-solving mindsetOwnership and accountabilityTeam mentorship and leadershipOptional / Additional SkillsOCR, ALATION, MuralServiceNow, JIRASemantic search and AI model evaluation

Bachelor’s degree in Engineering, Computer Science, Data Science, AI, or related field2+ years of experience in data science, AI engineering, and Generative AI systems