CX Analytics Lead

3 hours ago

Pasig, National Capital Region, Philippines Converge ICT Solutions Inc. Full time ₱2,000,000 - ₱5,000,000 per year

Role Overview

The CX Analytics Lead transforms fragmented customer data into predictive insights that drive measurable improvements in churn reduction, resolution performance, and customer loyalty. Moving beyond retrospective reporting, this role enables the organization to anticipate risks, detect silent sufferers, and guide proactive interventions that safeguard revenue and trust. By embedding advanced predictive models into daily operations, the role bridges raw data with executive decision-making, delivering actionable insights to strengthen service quality, enhance customer experience, and protect long-term revenue.


Key Responsibilities

1. Predictive Modeling & Analytics

  • Design, build, and validate predictive models for churn, NPS, DSAT, and case/ticket resolution outcomes.
  • Apply statistical and machine learning techniques (classification, regression, clustering, time-series forecasting) to uncover actionable insights.
  • Monitor and evaluate model performance using metrics like precision, recall, ROC-AUC, F1 score, and lift.

2. Data Integration & Management

  • Consolidate and transform data from multiple sources including CRM, ticketing systems, NPS surveys, billing, and network systems.
  • Ensure data quality, handle missing values, outliers, and perform feature engineering for robust modeling.

3. Customer Experience Insights & Operational Efficiency

  • Identify key drivers of dissatisfaction and escalations using advanced analytics.
  • Develop models to predict escalation risk or prolonged resolution times to support prioritization and resource allocation.
  • Collaborate with UX, product, support, and marketing teams to operationalize insights and improve service delivery.

4. Continuous Improvement & Innovation

  • Stay current with emerging tools, methods, and analytics trends.
  • Run pilot tests to validate new approaches and integrate successful techniques into operational workflows.
  • Translate model results into clear dashboards and reports for business stakeholders.

Qualifications

  • Bachelor's degree in Data Science, Statistics, Computer Science, Applied Mathematics, Industrial Engineering, Economics, or related field. Master's or postgraduate study is a plus.
  • 5+ years experience building predictive models for churn, customer retention, or loyalty.
  • Hands-on experience with customer support/case resolution analytics and customer feedback metrics (NPS, CSAT).
  • Strong statistical and machine learning foundation: regression, survival analysis, classification, clustering, time-series forecasting.
  • Experience with Python, R, SQL; familiarity with Spark/Hadoop is a plus.
  • Experience with sentiment analysis / NLP for free-text feedback.
  • Ability to operationalize models into business processes and dashboards, monitor performance, and iterate on models.
  • Strong analytical, project management, and cross-functional collaboration skills.
  • Experience in SaaS, e-commerce, telecom, or finance industries preferred.
  • Knowledge of causal inference, uplift modeling, and MLOps is a plus.

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