Manager, Segment, Revenue & Channel Insights

  • Competitive
  • Kuala Lumpur, Malaysia Kuala Lumpur Kuala Lumpur MY
  • Permanent, Full time
  • Hong Leong Bank Berhad
  • 23 Apr 18 2018-04-23

Manager, Segment, Revenue & Channel Insights

The position is part of Analytics team with view on optimizing Hong Leong's multi-channel sales and service delivery. The candidate will also be heavily involved in Hong Leong's omni-channel strategies aspiration in order to provide superior customer journey and increase efficiency of self-service terminals

Key Responsibilities

  • Demonstrate excellent ability in identifying trends and opportunities across all channel and previous experience in report and dashboard automation.
  • Produce meaningful marketing KPI dashboards and monthly performance reports with actionable insight.
  • Provide insights for customer behavior on usage, services and develop tactics for digital migration via self-service terminals.
  • Coordinate monthly reviews and manage business relationships with key stakeholders and partners in Segment, Digital Banking and Channel Teams
  • Participate in developing insights and strategies for omni-channel where customer execute " channel stitching " between digital, branches and self-service terminals
  • Participate in the development and application of channel behavior scorecards, pricing elasticity models, propensity models, CHAID analysis, cluster and regression statistical tools on different initiatives
  • Perform data extraction and analytics for the purposes of MIS reporting, campaign listing, campaign fulfillment, other communication listing extraction and analysis

Qualifications:

  • The successful candidate will need to have a strong background on Analytics and Reporting.
  • A strong background on Decision Management role is highly desirable
  • Minimum 3-5 years' experience in Segment or Channel Analytics in any industry. Experience in Banking and Insurance industry will be an added advantage.
  • Strong quantitative skills required including academic background in mathematics, statistics, business management, economics, engineering or other similar discipline.
  • Knowledge and previous experience with statistical modeling such as decision tree tools like CHAID or Logistic Regression is highly desirable
  • Knowledge of working with SAS, SQL or other programming languages.
  • Possess good writing and presentation skills