Deputy Manager of Data Analytics

JOB PURPOSE: Responsible for building a centralized reporting system, leveraging data for in-depth analysis, and developing data and machine learning models to support business activities (e.g., customer segmentation, behavior prediction). The role also involves deploying AI applications to enhance company-wide operational efficiency and decision-making.

KEY RESPONSIBILITIES:

1, Design & Implement Centralized Reporting System

• Develop and maintain management reporting systems and multi-level KPI dashboards (ExCo, departments, partners).
• Integrate data from multiple sources (MB Life core system, CRM, Apps, etc.) to ensure accuracy and consistency.
• Collaborate with departments to standardize reporting requirements and automate information flows.

2, Business Data Analysis

• Extract and analyze customer behavior and distribution channel data to optimize retention, cross-selling, reactivation, and improve CLV.
• Translate business questions into analytical problems and build end-to-end analytical frameworks.
• Execute or supervise segmentation models, lapse prediction, renewal behavior, upsell, and cross-sell models.

3, AI and Advanced Analytics Applications

• Lead implementation of AI/ML products: scoring, GenAI, fraud detection, automated underwriting, etc.
• Combine structured and unstructured data (digital footprints) to generate insights and behavioral models.

4, Process Development & Talent Building

• Establish processes to ensure efficient use and analysis of data across the company.
• Train teams of Data Analysts, AI Ops, and GenAI specialists under MBAL’s competency framework.
• Work closely with the Data Platform and Data Governance teams to ensure compliance with quality and security standards.

1, Education & Knowledge: Bachelor’s degree or higher in Data Science, Mathematics & Informatics, IT, Statistics, or related fields.

2, Experience:

• At least 5 years of working experience, including 3 years in a managerial role in Data Analytics/BI/AI teams.
• Experience in insurance, banking, or finance is preferred.

3, Technical Skills:

• Proficiency in SQL, Python, and BI tools (Power BI/Tableau).
• Hands-on experience in building reporting systems and deploying AI/ML models.
• Solid knowledge of data architecture (data mart, ETL), customer data, and digital behavior analytics.

4, Soft Skills: Strong communication and presentation skills, effective with both technical and executive audiences.

• Hình thức: Nhân viên chính thức