AVP, Distribution Transformation Insights & Engagement
MANULIFE (SINGAPORE) PTE. LTD.
Singapore, Singapore
Not specified (potentially hybrid or flexible based on company culture).
Performance measurement and business insights
Data modeling and roi measurement
Experimentation frameworks and causal inference
The AVP, Distribution Transformation Insights & Engagement position at Manulife Singapore offers an opportunity to enhance agency performance through data-driven insights and strategic decision-making. The role focuses on performance measurement, business insights, and operating model enhancement to drive growth and productivity
Job Summary
This role presents a high-impact opportunity to shape agency performance through data-driven insights and ROI-focused decision-making.
You will play a critical role in advancing the mission by translating complex data into actionable strategies that improve productivity and growth across agency channels.
The company empowers employees to learn and grow their careers in a flexible environment where well-being and inclusion are prioritized.
Matching Summary
Match Score: 85
The AVP, Distribution Transformation Insights & Engagement position at Manulife Singapore offers an opportunity to enhance agency performance through data-driven insights and strategic decision-making. The role focuses on performance measurement, business insights, and operating model enhancement to drive growth and productivity.
Skills & Requirements
Must-have
Performance measurement and business insights
Data modeling and ROI measurement
Experimentation frameworks and causal inference
Lead funnel performance optimization
Data engineering and instrumentation
Nice-to-have
Cross-functional collaboration skills
Ability to translate ambiguous problems
Strong strategic decision-making support
Experience with A/B testing methodologies
Key Requirements
Proven experience in performance analytics or business insights roles
Strong analytical skills with comfort in data modeling
Experience with experimentation frameworks and causal inference methodologies