Position Overview:
The Vehicle Data & Analytics Specialist plays a key role in building, enriching, maintaining, and improving automotive aftermarket data across East Asia, including vehicle data, OE (Original Equipment) application data, and Bosch product application data. Acting as a regional focal point for vehicle-related data activities, the role works closely with country teams, external data providers, and internal stakeholders to improve data coverage, quality, consistency, and related processes.
Based on department priorities and internal customer needs, the role applies data analysis tools and methods, including Power BI, Python, and SQL, to identify data gaps and business needs, and translate findings into executable data actions such as data collection, research, supplier follow-up, and joint actions with relevant stakeholders.
The position is a hands-on data role supporting Product Management, Marketing, Sales, and Management with reliable automotive aftermarket data, analysis, and reporting, while continuously improving regional data processes and usability.
Key Responsibilities
1. Vehicle Data development and Management
- Develop and maintain centralized automotive aftermarket data for East Asia, with primary focus on Japan and Korea, ensuring data accuracy, coverage, and accessibility.
- Build and enrich datasets including vehicle, OE, VIO, material, product application data.
- Work with external data providers and internal stakeholders to collect, validate, integrate, and continuously improve data coverage.
- Identify data gaps through analysis and research, use relevant intelligence sources and methods to enrich missing or incomplete information, and drive follow-up actions.
2. Data Analytics
- Translate department priorities and internal customer needs into structured data analysis using Power BI, Python, SQL, and other relevant tools.
- Analyze Automotive Aftermarket and related business data to identify gaps, trends, patterns, and improvement opportunities.
- Provide data-based insights and recommendations to support Product Management, Marketing, Sales, and Management.
- Turn analytical findings into executable data action plans and work schedules, to follow through with relevant stakeholders.
3. Data Quality & Reporting
- Monitor and improve data accuracy, completeness, consistency, and coverage through regular validation and quality checks.
- Identify data-quality issues and root causes, and coordinate corrective actions with internal stakeholders and external data providers.
- Apply established data standards and support continuous improvement.
4. Process & Continuous Improvement
- Prepare and maintain regular and ad-hoc reports, Power BI dashboards, and analytical outputs based on department and internal customer requirements.
- Support regular & add-hoc data operations and delivery requirements, including catalogue, application, and other internal or external data outputs.
- Improve data workflows, quality, and efficiency through standardization, automation, and appropriate analytical tools.
- Maintain clear documentation of key data sources, definitions, processes, and working procedures to support consistent and scalable data operations.