Data Scientist

*) Analyze Google CES CCaaS / CCAIP interaction data in BigQuery to optimize call routing, channel strategy, and service outcomes using historical patterns, time-of-day trends, and customer profiles.

*) Analyze unstructured voice and text data from calls, chats, emails, and case notes to determine sentiment, identify pain points, and uncover service drivers.

*) Develop predictive models for call volume, queue pressure, churn risk, and intent classification to improve staffing and proactive service strategies.

*) Evaluate Time To Resolution (TTR), escalation trends, and process bottlenecks using linked BigQuery datasets and operational measures surfaced through Looker.

*) Enhance AI tools, virtual assistants, and knowledge recommendations by using analytics from interaction outcomes and customer behavior.

*) Apply GA4 and cross-channel behavioral data where relevant to understand customer journey transitions between digital self-service and assisted support.

*) Present findings, experiments, and recommendations through analytical narratives, dashboards, and executive-ready reporting.

*) High proficiency in Python and/or R, with expertise in SQL and BigQuery.

*) Knowledge of predictive modeling and statistical analysis, including NLP for call transcripts, chat transcripts, and case notes.

*) Ability to present findings and build shareable reports using Looker, Tableau, Power BI, or similar business intelligence tools.