Deskripsi Pekerjaan
Join Indospec Asia as a Maintenance Data Analyst and become a key driver in optimizing our operational efficiency through data-driven insights. This critical role bridges maintenance operations and data science, transforming raw equipment data into actionable strategies that minimize downtime, reduce costs, and enhance asset reliability. You'll leverage advanced analytics to identify failure patterns, predict maintenance needs, and implement preventive measures across our industrial infrastructure. Collaborate with engineering teams to develop KPI dashboards, automate reporting systems, and present complex findings to stakeholders. If you're passionate about using data to solve real-world maintenance challenges and thrive in a fast-paced industrial environment, this opportunity is for you.
Tanggung Jawab
- Analyze maintenance data from CMMS, IoT sensors, and work orders to identify failure patterns and root causes
- Develop predictive maintenance models using statistical analysis and machine learning techniques
- Create automated dashboards and reports for KPIs like MTBF, MTTR, and asset utilization
- Collaborate with cross-functional teams to implement data-driven maintenance strategies
- Monitor equipment performance trends and recommend preventive/corrective actions
- Optimize maintenance schedules and resource allocation based on data insights
- Document analytical methodologies and ensure data integrity across systems
Kualifikasi
- Bachelor's degree in Industrial Engineering, Data Science, Statistics, or related field
- 3+ years experience in maintenance data analysis or industrial data analytics
- Proficiency in SQL, Python (Pandas, Scikit-learn), and data visualization tools (Tableau/Power BI)
- Strong knowledge of maintenance methodologies (RCM, TPM) and asset management systems
- Experience with time-series analysis and predictive modeling for industrial equipment
- Certification in data analysis or maintenance management preferred
- Excellent problem-solving skills with attention to operational context