Top Data Analyst Jobs in Malaysia

Translate business needs into analytics, reporting, and AI-enabled insights. Analyze data with Python and SQL, develop Power BI dashboards and semantic models, and create governed datasets. Design and evaluate GenAI, LLM, Copilot, and AI-agent use cases using RAG, vector databases, Microsoft Fabric, Azure AI Foundry, and related platforms. Partner with stakeholders and engineering teams to support enterprise AI adoption, automate workflows, and shape the organization’s APAC AI strategy.

Develops and standardizes commercial dashboards, reports, and analytics to support business decisions. Aggregates and validates data from multiple sources, maintains data integrity, manages reporting requests, and recommends process improvements. The role also supports data stewardship and governance initiatives, improves data adoption and maintenance, and resolves duplicate or improperly assigned records. Collaboration with stakeholders, data manipulation, dashboard creation, and business insight generation are central responsibilities.

Analyze complex business data to establish monitoring frameworks, identify business issues, and deliver actionable insights for operational decisions, marketing strategies, and product direction. Develop analysis methods, define data product requirements, collaborate with product and development teams, support project execution, and provide training on data concepts, tools, and methods.

Lead design, build, and maintain factory automation and connectivity solutions for semiconductor back-end production. Implement AI controllers, image AI, SCADA and remote command center capabilities. Integrate hardware (AGV/ARV/ASRS), collaborate with engineering and data science to deploy predictive quality and maintenance, convert business needs to IT specs, manage stakeholders, roadmap factory automation, and monitor project delivery.

Monitor customer service KPIs, analyze data for insights, optimize systems, support AI tools, and collaborate with teams for reporting and improvements.

Manage Engineering Change Orders, product and parts data, BOM structures, document releases, and product lifecycle processes across ERP and PLM systems. Coordinate with Engineering, Production, Procurement, Supply Chain, Marketing, and Product Support to ensure data integrity and manufacturing readiness. Support new product introductions, product obsolescence, compliance, KPI improvement, and continuous improvement initiatives. Lead related projects and provide internal consulting on product structure and configuration management.

Provide day-to-day Aras PLM operational support, troubleshoot user issues, manage product master data and governance, analyze and improve business processes, gather requirements for system changes, support testing and UAT, create process documentation and training, and liaise between business and IT across global semiconductor teams.

Support APAC Claims Operations by producing and automating reports, reconciling multi-system data, resolving quality issues, and developing scalable dashboards. Build SQL queries, Python automation workflows, data validation processes, and documentation. Deliver ad hoc analysis and leadership insights while piloting AI applications such as claims classification, anomaly detection, document summarization, and natural-language querying. Partner across markets to improve reporting efficiency, data quality, and operational decision-making.

As a Data Analyst, your role involves analyzing sales data, developing data-driven insights, collaborating with sales teams, and creating visualizations to communicate insights effectively.

Analyze business requirements, lead data mapping and source-to-target transformations, develop and optimize complex SQL queries, define data quality controls, support UAT and testing, prepare documentation, and coordinate stakeholders to ensure accurate data integration and reporting for banking projects.

The Data Analyst role involves annotating emails, identifying malicious URLs, labeling data for AI training, ensuring process adherence, and supporting project management KPIs.

This Data Analyst role involves annotating and examining emails, identifying malicious links, labeling data for AI, and ensuring compliance with processes. The candidate will also monitor KPIs and assist project management.

As a Data Analyst at Oliver Wyman, you will work with clients to solve challenges through data analytics, including developing prototypes and sharing insights. You will participate in diverse projects involving machine learning, risk management, and customer analytics.

The Senior Data Analyst will design analyses, develop reporting solutions, gather customer feedback, and improve customer experience through data-driven strategies.

Supports data science and analytics solution development that drives business growth, customer experience, productivity, and efficiency. Responsibilities include delivering analytics workplans, developing statistical, predictive, segmentation, and propensity models, creating reusable best practices, supporting business decisions, and collaborating with multidisciplinary teams. The role requires programming-based analytics expertise, machine learning knowledge, strong analytical and problem-solving skills, business acumen, and project management capabilities.

First-line data center operations role responsible for 24/7 monitoring and maintenance of critical electrical and mechanical systems, incident response, vendor oversight, ticket support, reporting, asset management, audits, and remote-hand/server tape tasks.

As a Communications Data Analyst Intern, support data reporting, assist in email campaigns, maintain databases, and help with operational communications.

Analyze data to mitigate risks, develop insights on user behaviors, maintain business metrics, create dashboards, and collaborate on risk management strategies.

Assist in developing growth strategies and optimizing processes in the Borneo region with strong analytical skills and collaboration efforts.

As a Senior Analyst, you will consolidate and ensure data integrity while collaborating with finance teams to develop solutions that meet business needs.