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Salary
≈ $22k – $45k per year (Estimated)
Location
In office (Gurgaon)
Seniority
Senior · 7+ years exp

Confirmed on the employer's own hiring board on Oct 23, 2026. First seen by Alion on Aug 21, 2026. EXL scores B on the Alion truth index.

Overview
Company
Impact
Profile match

EXL

EXL, legally ExlService Holdings, is a data analytics, AI and digital operations company headquartered in New York that runs outsourced business processes and builds data and AI solutions for insurers, healthcare organisations, banks, media and retail companies. Founded in 1999 and listed on Nasdaq, it has more than 60,000 employees across six continents, with large delivery centers in Noida, Gurgaon, Pune, Bengaluru and Chennai and a newer AI hub in Dublin. It hires data scientists and data engineers, GenAI and MLOps engineers, analytics managers, solution consultants and client partners, plus talent acquisition, finance and medical coding staff.

Core Responsibilities

Client & Program Leadership

  • Serve as primary client partner for analytics engagements, shaping problem statements, defining success criteria, and managing executive updates.
  • Translate business goals into data science roadmaps and measurable outcomes.
  • Establish and run program governance (steering committees, RAID logs, change control, dependency management).

Delivery & Value Realization

  • Own scope, plan, and delivery across multiple workstreams; track timelines, budgets, and outcomes; ensure on-time, on-budget delivery.
  • Define value baselines and benefit tracking .
  • Lead end-to-end development of AI/ML models including problem formulation, data exploration, feature engineering, model training, validation, and deployment.
  • Design and implement predictive, prescriptive, and generative AI solutions using structured and unstructured data.
  • Drive adoption of ML best practices, including model explainability, fairness, bias detection, and performance monitoring.

Data Science & MLOps Leadership

  • Lead end-to-end development of AI/ML models including problem formulation, data exploration, feature engineering, model training, validation, and deployment.
  • Design and implement predictive, prescriptive, and generative AI solutions using structured and unstructured data.
  • Drive adoption of ML best practices, including model explainability, fairness, bias detection, and performance monitoring.
  • Architect and oversee production-grade ML pipelines using MLOps principles.

Professional certification such as CA, CPA, CISA or CIA. 7-9 years of experience.

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