Data Analyst (AI)

Hartalega; Sepang; On-site; MYR 120,000 - 180,000; Full time

Job summary

Hartalega in Malaysia is seeking a data scientist to extract insights from operational data and drive AI initiatives across the business. This role bridges IT processes with external technology vendors, ensuring data readiness and advising on AI methodologies.

Responsibilities include cleaning data pipelines for ML readiness, implementing production ML/AI algorithms, training and deploying models, and building dashboards to monitor KPIs and model drift.

Qualifications

• Bachelor’s degree required in data science or related field.
• Minimum 4 years in data analysis or ML-focused role.
• Experience evaluating data for visualization.
• Familiarity with Grafana, Node-RED, InfluxDB, BI tools preferred.
• Certifications in Data Science/ML/Cloud are advantageous.

Responsibilities

• Assess and clean data pipelines for ML/AI readiness.
• Implement ML/AI algorithms using production data.
• Lead training and deployment of AI/ML models.
• Manage data deployments across cloud and on-premise environments.
• Design test plans to validate model accuracy and viability.
• Perform exploratory data analysis to identify trends and opportunities.
• Develop dashboards to track KPIs and model drift.
• Enforce data governance and security per Hartalega policies.
• Collaborate with IT and engineers to resolve data quality issues.
• Maintain project documentation and secure design file systems.

Skills

Data analysis

ML/AI

Dashboard design

Data governance

Stakeholder comms

Python programming

Education

Bachelor's degree in data science or related field

Tools

Grafana

Node-RED

InfluxDB

PowerBI

Tableau

Job description

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.