Jobs at EXL

Manage end-to-end CRM lifecycle: campaign strategy, segmentation, build/deploy for outbound channels (email/SMS/push), A/B and multivariate testing, lifecycle optimization, performance measurement, and cross-functional collaboration to grow fan engagement and lifetime value.

Design, develop, and optimize complex Oracle SQL queries, views, stored procedures, and packages to power marketing analytics. Support audience selection, segmentation, suppression logic, and campaign tracking. Collaborate with marketing, analytics, and data science teams; provide production support, troubleshooting, root-cause analysis, and ensure data accuracy and performance across large datasets.

Support international data initiatives by performing SQL-based analysis, producing insights and executive-ready scorecards, maintaining reporting/operational dashboards, coordinating incident management and operational readiness, and aligning cross-functional stakeholders to drive data-driven decisions across global markets.

Lead design and delivery of end-to-end ML solutions for insurance (claims, underwriting, sales). Own feature engineering, model selection, training, validation, and handling imbalanced/weak-label data. Ensure explainability, governance, and production readiness. Act as client-facing data scientist, coordinate offshore teams, contribute to MLOps, model monitoring, and deployment on cloud analytics platforms.

Lead end-to-end delivery of large-scale analytics and data management programs: enforce delivery best practices, manage multi-workstream teams, liaise with senior stakeholders, ensure quality/performance on cloud data platforms, and drive account growth and talent development.

Design, build, and operate production-grade Generative and Agentic AI applications and services. Build backend services in Python, integrate LLM APIs and agent frameworks, implement RAG pipelines and vector search, ensure reliability/security/observability, deploy on major clouds, and mentor junior engineers.

Design, build, and operate production-grade Generative and Agentic AI applications and services. Develop backend services in Python, integrate LLM APIs and agent frameworks, implement RAG and vector search, deploy on major clouds, ensure reliability, observability, and mentor junior engineers.