Chubb Life HK - Head of Customer Insights

  • A strategic role leading Customer Insights team to look at end-to-end customer strategy via deep dive in customer and data insights
  • Ability to lead and conduct market research via research house, desk research or internal survey platform
  • Develop and present customer insights based on data analysis to support development of customer propositions
  • Collaborate with cross-functional teams including marketing, operations, agency, partnership, product development and finance, to understand their data needs and provide actionable insights
  • Oversee the ongoing maintenance, enhancement, and operational reliability of the data ingestion pipeline
  • Oversee the design, development, and implementation of advanced analytics and data solutions
  • Lead, inspire, and develop a team of data and analytics professionals
  • Serve as the primary point of contact between the Global Data team and the market stakeholders for data initiatives
  • Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related field
  • More than 10 years of experience in data analytics, data science, data engineering or a similar role, with experience in the life insurance industry being a plus
  • Solid and practical experience in customer experience, CRM, and data & analytics
  • Profound data & analytics, and insight summary skills
  • Demonstrated ability to work, communicate and influence across functions and multiple stakeholders
  • Good communication, and presentation skills
  • Ability to deal with complexity and ambiguity
  • Proactive and willing to take challenges and enjoy exploring new things
  • Ability to turn consumer insights into business recommendations
  • Strategic thinking, fast learner and problem solving skills
  • People management experience; be able to develop talents
  • Familiar with various research tools
  • Comfortable working with all levels of management
  • Ability to conduct English presentation & reports is required
  • Strong proficiency in data visualization tools, analysis tools and programming languages, such as Power BI, SQL and Python
  • Proven experience in data engineering or data platform engineering
  • Strong understanding of data pipelines, data wrangling, data transformation, and ETL processes

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