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

Qualifications

• 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