WNS Global Services
Intelligent operations and transformation
SeniorAssociate-Analytics
Neural analysis suggests this role is
optimal for mid candidates.
“Senior Associate-Analytics at WNS Global Services. Skills: Python, Data Automation, AI Operations, LLM workflows. Support and maintain production automation and AI-driven data processing workflows. Monitor Python-based automation pipelines”
What You'll Achieve.
enable lasting business value by designing intelligent, human-led solutions that deliver sustainable outcomes and a differentiated impact
Industry & Context.
Strong analytical and problem-solving mindset
What They're Looking For.
Must Have
Python (Advanced), Data Wrangling & Data Analysis, Production automation, FastAPI or similar backend frameworks, LLM workflows, prompt engineering, and RAG concepts, Vector databases exposure (e. g. , Pinecone), Git, Docker, Postman, cURL, cloud platform exposure, Excel, Communication Skills, Strong analytical and problem-solving mindset, Attention to detail, Ownership and accountability, Bachelor’s degree in Engineering, Computer Science, Data Science, AI or related field, 1–4 years of experience in automation, data engineering, or AI operations roles
Nice to Have
SQL, Power Bi, Jira, Semantic search and AI model evaluation knowledge
What You'll Do.
Support and maintain production automation and AI-driven data processing workflows
Monitor Python-based automation pipelines
Troubleshoot production issues
Assist in optimization of LLM-enabled and document/data processing systems
Monitor and support production automation pipelines developed using Python and FastAPI
Perform L1/L2 troubleshooting for automation scripts
Identify and resolve script failures
and performance issues in distributed systems
Process and validate structured and semi-structured data from multiple sources (Excel
Perform data normalization
Investigate and resolve data inconsistencies impacting downstream workflows
Support LLM-based automation workflows including prompt optimization and token management
Assist in RAG systems by validating embeddings and debugging semantic search relevance
Review and improve LLM output quality
Use Git for version control (branching
Perform basic Docker operations such as container inspection and log analysis
Test and debug APIs using Postman and cURL
Prepare incident reports
root cause analysis (RCA)
and escalation summaries
How You'll Work.
Team & Collaboration
Collaborate with business, data, and engineering teams
Communication Scope
Communication Skills
Full Job Description
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. About the RoleWe are looking for a detail-oriented Senior Associate – Data Automation & AI Operations to support and maintain production automation and AI-driven data processing workflows. This role involves monitoring Python-based automation pipelines, troubleshooting production issues, and assisting in optimization of LLM-enabled and document/data processing systems.This role is ideal for professionals with 1+ years of experience in automation, data engineering, or AI operations who are comfortable working in production environments and collaborating with cross-functional teams.Key ResponsibilitiesAutomation & Production SupportMonitor and support production automation pipelines developed using Python and FastAPIPerform L1/L2 troubleshooting for automation scripts, APIs, and data workflowsIdentify and resolve script failures, dependency conflicts, API errors, and logic edge casesAnalyze logs, error traces, and performance issues in distributed systemsData Processing & ValidationProcess and validate structured and semi-structured data from multiple sources (Excel, CSV, APIs)Perform data normalization, deduplication, and
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