Position Overview:
The Regional Data Analytics Specialist translates Mobility Aftermarket business priorities and requirements from the department and Regional Headquarters into structured analytical approaches, clarifying and structuring requirements where appropriate.
The role integrates and analyzes vehicle, product, product marketing, and sales data across markets to identify performance drivers, gaps, trends, and business opportunities, and to develop meaningful cross-market and regional insights.
The role translates analytical findings into actionable business insights and recommendations, and supports relevant stakeholders in translating insights into actions and tracking progress.
Based on business needs, the role develops and maintains analytical solutions using Power BI, Python, SQL, structured working files, and other appropriate digital tools to enable effective reporting, analysis, and decision-making across East Asia.
The role also supports the improvement of regional data processes and workflows through database solutions, ETL, automation, and other appropriate technologies.
Key Responsibilities
1. Regional Business Analytics & Reporting
- Perform cross-market analysis of vehicle, product, product marketing, sales, and related business data to identify performance trends, gaps, and opportunities.
- Own and maintain recurring regional reports, KPI dashboards, Power BI solutions, and structured working files to support regional business and management requirements.
- Develop common analytical logic, data models, and reporting views to enable consistent cross-market comparison and regional performance analysis.
- Conduct ad-hoc and project-based analysis and deliver clear, actionable insights to Product Management, Marketing, Sales, and Management.
2. Data Integration & Analytical Solutions
- Integrate, standardize, and prepare data from different markets and sources to support regional analytics and reporting.
- Develop and maintain data processing and ETL workflows using Python, SQL, and PostgreSQL, including structured datasets and database solutions for recurring analytical needs.
- Automate repetitive data preparation and reporting processes and develop reusable analytical solutions to improve data availability, consistency, and efficiency.
- Maintain data logic, definitions, and technical documentation to ensure reliable and sustainable analytical operations.
3. Digital Solutions & Continuous Improvement
- Develop practical digital and data applications, including database-connected web-based tools, to support business analysis and user interaction with data.
- Improve existing analytical workflows and solutions through appropriate technologies, automation, and user-oriented design.
- Explore and apply relevant technologies, including AI-enabled tools, to improve data analysis, business processes, and operational efficiency.