EXL—Lead Assistant Manager

Job description

Description: We are seeking a Modeler to contribute to the development of AI/ML solutions that improve contact center efficiency and member experience. You will build and optimize models supporting call deflection, intelligent routing, agent assist, and quality monitoring initiatives. Working in a collaborative team environment, you will apply machine learning and NLP techniques to operational data and support the full model development lifecycle. Requirements: - 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. 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.