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Lead Assistant Manager

EXL Service
Gurugram, IND
Full-time
Mid · 3+ years experience
Onsite
Discovered Yesterday
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Responsibilities

  • Develop and optimize machine learning models for call deflection prediction, intelligent routing, and automated quality monitoring.
  • Apply NLP techniques to analyze call transcripts and digital interaction logs to classify intent, detect topics, and surface automation opportunities.
  • Perform feature engineering on structured and unstructured operational data sources including CRM records, call logs, and interaction metadata.
  • Support end-to-end model lifecycle activities including data preparation, model training, evaluation, documentation, and performance monitoring.
  • Design and execute A/B tests or champion-challenger evaluations to measure model impact on operational KPIs.
  • Collaborate with contact center operations and technology teams to understand workflows and integrate model outputs into existing systems.
  • Prepare clear model documentation covering methodology, assumptions, performance metrics, and monitoring plans.
  • Monitor deployed models for drift and degradation, escalating issues and recommending retraining or recalibration as needed.
  • Stay current on advances in conversational AI, NLP, and operational analytics.

Qualifications

  • 3–6 years of experience in data science, analytics, or machine learning with exposure to operational or contact center domains.
  • Working knowledge of NLP techniques including text classification, entity extraction, and sentiment analysis.
  • Proficiency in Python; familiarity with libraries such as scikit-learn, spaCy, Hugging Face, pandas, and numpy.
  • Experience with SQL and working with large, complex operational datasets.
  • Understanding of contact center metrics such as handle time, first-call resolution, CSAT, and deflection rates is preferred.
  • Familiarity with model validation concepts, performance evaluation frameworks, and documentation standards.
  • Strong analytical and problem-solving skills with a practical, solutions-oriented mindset.
  • Effective communication skills for presenting analytical findings to both technical peers and operational stakeholders.
  • Bachelor's degree (Master's preferred) in Computer Science, Statistics, Engineering, or a related quantitative discipline.

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