To transform manufacturing and operational data into actionable insights by developing robust data models, dashboards, and analytics solutions. The role supports data-driven decision making, ensures data governance compliance, and enables PMO & Data Excellence initiatives across production and engineering functions.
Key Responsibilities
Data Analytics & Insight Generation
- Analyze manufacturing, quality, operational data, and product development data to identify trends, patterns, and improvement opportunities
- Develop dashboards and reports (e.g., Power BI/Tableau) for real-time performance monitoring
Data Management & Governance
- Ensure data accuracy, consistency, and compliance with company data standards
- Define and maintain data structures, data models, and quality data structure.
- Collaborate with IT/OT teams to improve data pipelines and system integration
- Ensure PDPA and internal policy compliance
PMO & Project Analytics Support
- Provide analytics support for improvement initiatives, tracking (project performance, KPI monitoring, ROI tracking)
- Develop standardized reporting frameworks for strategic initiatives (e.g., automation, AI, cost reduction)
- Support strategic initiative feasibility/ business case development with data-driven insights
Advanced Analytics & Digital Enablement
- Apply statistical methods and basic machine learning models for forecasting and optimization
- Support AI/automation projects by preparing and validating datasets
- Contribute to building a scalable data ecosystem (e.g., data lake, cloud platforms)
Cross-functional Collaboration
- Work closely with Production, Quality, Engineering, Product Development , Finance and IT dev. teams,
- Translate business problems into data analytics solutions
- Support stakeholder decision-making through clear data storytelling
Qualification
Bachelor's Degree or higher in Engineering, Data Science , AI, Applied Math, Computer Engineering, Computer Science or other related fields.Pivotal (Must-have)- Strong skills in data analysis (SQL, Python, Power BI/Tableau)
- Understanding of data modeling, Extract , Transform, Load processes, and database structures
- Experience in manufacturing or operations data analysis
- Knowledge of statistical analysis and problem-solving techniques
- Ability to translate data into business insights and recommendations
- Experience with cloud platforms (Azure, Databricks, Fabric)
- Exposure to AI/ML or predictive analytics use cases
- Familiarity with data governance frameworks
- Experience supporting PMO or transformation projects
- Proficiency in Python programming for AI/ML development
- Experience in data handling and analysis tools (e.g., NumPy, Pandas)
- Basic understanding of databases (SQL, SparkSQL) for data storage and retrieval
- Experience with version control systems (e.g., Git)
- Familiarity with model deployment concepts (e.g., API integration, edge devices, or cloud platforms)
- Professional (Nice-to-have)
- Hands-on experience in real-world Computer Vision or AI/ML projects
- Experience working with large-scale or complex datasets
- Understanding of system integration concepts (e.g., connecting models with applications or hardware)
- Familiarity with MLOps concepts (e.g., model versioning, monitoring, retraining pipelines)
- Experience working in cross-functional teams (e.g., engineering, product, or research)
- Experience collaborating with external partners, universities, or research organizations
- Understanding of domain-specific applications (e.g., manufacturing, healthcare, retail, or smart cities)
