Data Analyst (AI)

Job Purpose:

Responsible for extracting, evaluating, and transforming operational data into actionable insights while playing a pivotal role in Hartalega's AI and machine learning initiatives. This role will act as a bridge between internal processes and external technology vendors, ensuring data readiness and advising on the best AI methodologies.

Responsibilities:

• Assess and clean data pipelines to ensure readiness for ML/AI applications.
• Implement optimal ML/AI algorithms using production data to meet process requirements.
• Lead the training and deployment of AI/ML models in production environments.
• Manage data deployments across cloud and on-premise environments, supporting vendor-led AI initiatives.
• Design and execute rigorous test plans to validate the accuracy and commercial viability of AI models before deployment.
• Perform exploratory data analysis (EDA) to identify trends, anomalies, and optimization opportunities in manufacturing.
• Develop and optimize interactive dashboards to track KPIs, operational metrics, and AI model drift.
• Enforce data governance, documentation, and security standards per Hartalega policies.
• Partner with IT and manufacturing engineers to gather requirements and resolve data quality issues.
• Ensure all project documentation is completed accurately. Manage and secure the design drawing/file system in compliance with IT policies. Any other tasks relevant to your skillset that assigned by your superior.

Qualification & Experience:

• Bachelor’s degree in data science, Computer Science, Statistics, Mathematics, Information Technology, or a closely related quantitative field.
• Minimum 4 years of relevant working experience in data analysis, data engineering, or a machine learning-focused role.
• Strong capability in evaluating data to determine the optimal visual presentation strategy.
• Hands-on knowledge and practical experience with Grafana, Node-RED, and InfluxDB will be considered a significant added advantage, alongside familiarity with other BI tools (e.g., PowerBI, Tableau).
• In-depth knowledge of ML methodologies (supervised/unsupervised learning, predictive modelling, deep learning) and the ability to recommend best-fit algorithms for industrial applications.
• Competent with high integrity and strong analytical skills;
• Result-oriented with the ability to work independently with all levels of employees.
• Demonstrate high leadership and managerial skill, especially identifying tackling and presenting issues.
• Certifications in Data Science, Machine Learning, or Cloud Infrastructure (Oracle, Huawei, AWS, Azure) are highly advantageous.