Lead Assistant Manager

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.
• - 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.