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Senior Customer Analytics Manager, Insurance

Morgan McKinley Hong Kong
Full time Permanent On-site Competitive

About the job

Job Responsibilities

Data Product Owner & Predictive Modeling
  • Lead Predictive Analytics Roadmaps: Partner with the Director to prioritize and manage data products, including lead scoring, propensity models, next-best-action, upsell/cross-sell engines, and Customer Lifetime Value (LTV) models.
  • Industrialize Analytics: Establish scalable processes, automation frameworks, and model deployment standards across various business units.
  • Model Governance: Collaborate with Data Science teams to ensure predictive models are explainable, operationally scalable, and consistently monitored for performance, retraining, and fairness checks.
Customer Strategy & Growth Insights
  • Lifecycle Optimization: Conduct deep-dive analyses to uncover insights that drive customer acquisition, engagement, and long-term retention.
  • Advanced Segmentation: Build and refine advanced customer segmentation frameworks to support targeted multi-channel marketing and highly personalized policyholder communications.
  • Customer Journey Analytics: Work with Customer Experience (CX) and Digital product teams to map digital footprints (e.g., app, e-commerce, customer portal), quantify drop-off touchpoints, and resolve repeat contact drivers.
Campaign Measurement & Experimentation
  • Own Campaign Measurement: Design evaluation frameworks for digital and CRM marketing campaigns using attribution modeling, incrementality testing, and Marketing Mix Modeling (MMM) to optimize budget allocation.
  • Run A/B Testing: Design and execute structured experimentation libraries (e.g., A/B testing, multi-armed bandits) across web platforms, applications, push notifications, and call center scripts.
Cross-Functional Stakeholder Management
  • Act as the Core SME: Serve as the Subject Matter Expert (SME) and primary bridge connecting Marketing, Product Development, and Business Units with Data Science, Data Engineering, and IT teams.
  • Translate Data for Executives: Translate technical metrics and complex data findings into practical, executive-ready presentations and dashboards (using Power BI or Tableau) to influence senior leadership decisions.
Data Infrastructure & AI Transformation
  • Standardize Customer Data Foundations: Partner with Data Engineering to build robust data pipelines (e.g., via Spark or Databricks) ensuring that transactional, behavioral, and research data are integrated, secure, and standardized.
  • Drive AI & Automation: Support the implementation of GenAI and automation initiatives that elevate operational efficiency and automate recurring "signal" reports.
  • Data Governance & Privacy: Ensure all deployed customer analytics products comply strictly with regional data privacy laws, governance guidelines, and insurance compliance standards
Job Requirements
  • Bachelor's degree holder
  • A minimum of 12 years of relevant experience gained from large insurance firms
  • Fluent Chinese and English