We are Lenovo. We do what we say. We own what we do. We WOW our customers.

Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).

Key Responsibilities

• Collect and analyze manufacturing quality data across systems and global sites.
• Develop and maintain dashboards, reports, and basic data analysis tools.
• Monitor quality KPIs, defect rates, failure trends, and manufacturing performance.
• Use statistical analysis and data visualization to identify trends and quality issues.
• Support root cause analysis and corrective actions with Engineering, Manufacturing, and Quality teams.
• Assist with quality process improvements and reporting standardization across sites.
• Support continuous improvement initiatives for product quality and manufacturing efficiency.
• Assist with customer quality investigations, reporting, and communication.

Qualifications

• Bachelor’s or Master’s degree in Engineering, Data Science, Statistics, or a related field.
• Fresh graduates are welcome to apply.
• Basic knowledge of data analysis, statistics, and problem-solving.
• Proficiency in Excel; experience with Power BI, Python, SQL, Minitab, or Tableau is a plus.
• Strong communication skills and ability to work with cross-functional and global teams.
• Good written and spoken English.
• Interest in manufacturing, quality engineering, and data analytics.