Why Work at Lenovo

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

Lenovo is a US$57 billion revenue global technology powerhouse, ranked #248 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).

• Responsible for cybersecurity responsibilities and data analysis for cybersecurity logs
• Provide IT security consultancy and advisory to Agency.
• To assist agency to consolidate, track and report the status of security advisory received from GITSIR, CSA, NCSC etc.
• Follow up with respective Facilities Management Team on the implementation of the remediation against the security advisory received, IOC scanning and reporting, patching of the system and vulnerability for systems in HQ DC.
• Provide ad hoc, monthly report for Privilege Access Manager, Early Detection and Response solution, Database Activities Monitoring, log review, account review etc.
• Review of logs capture in the syslog server from all the systems
• Support IT security audit, compliance audit, and security related matters.
• Work on quarterly Vulnerability scanning and remediation with ATFM and provide reporting and track the status.
• Share domain and technical expertise, providing technical mentorship and cross-training to other peers and team members.

• Preferable min. 2-3 years of working experience, preferably in the SI environment.
• Diploma or Bachelor's degree in a quantitative field like statistics, mathematics, computer science, economics, or a related field is typically required.
• Proficiency in at least one data analysis language like Python (with libraries like Pandas, NumPy, Scikit-learn) or R.
• SQL for querying databases, and potentially experience with tools like Excel or data manipulation libraries.
• Experience with tools like Tableau, Power BI, Qlik Sense, or data visualization libraries in Python (e.g., Matplotlib, Seaborn).
• Familiarity with statistical software packages like SPSS or SAS can be beneficial.
• Knowledge of Hadoop, Spark, or other big data technologies may be required for roles dealing with large datasets.
• Strong analytical and problem-solving skills are crucial for interpreting complex data and drawing meaningful insights.
• Excellent written and verbal communication skills are necessary to present findings clearly and concisely to both technical and non-technical audiences.
• Depending on the industry, having domain-specific knowledge (e.g., IT and finance) can be a significant advantage.