Job Description
Job Purpose
To support datadriven decision-making by analysing operational and business data, building dashboards, and identifying process improvements. This role combines data analytics with industrial engineering methodology to improve efficiency, reduce waste, and enhance overall business performance in Logistics.
Key Responsibilities
Data Analysis & Modelling
- Analyse operational, production, supply chain, and business datasets.
- Build performance models, forecasts, and basic statistical analyses.
- Conduct rootcause analysis using data-driven insights.
- Identify patterns, gaps, and efficiency opportunities.
Reporting & Visualisation
- Build and maintain dashboards in Power BI / Tableau / Qlik.
- Develop automated reporting processes.
- Present insights clearly to management and crossfunctional teams.
- Track and measure KPIs and operational performance.
Process Improvement (Industrial Engineering Focus)
- Apply Lean, Six Sigma, workflow mapping, and IE tools to analyse processes.
- Assist in designing and implementing improvement solutions.
- Support optimisation projects such as throughput improvement, cost reduction, layout optimisation, etc.
- Conduct time & motion studies where necessary.
Data Management & Governance
- Clean, validate, and maintain data quality.
- Collaborate with IT/data teams to improve data structures.
- Document datasets, dashboards, and analytical processes.
Cross-Functional Collaboration
- Work closely with Operations, Finance, Supply Chain, and IT.
- Support project teams with quantitative analysis.
- Contribute to continuous improvement initiatives and action planning.
Minimum Qualifications
- Bachelor’s Degree in Industrial Engineering (essential).
- Additional qualifications in Data Analytics, Business Intelligence, or Statistics (advantageous).
- Certifications in Power BI, SQL, Lean Six Sigma, Python are beneficial.
Required Skills & Competencies
Technical Skills
- Strong analytical and problemsolving ability.
- Advanced Excel.
- Power BI / Tableau / Qlik dashboarding experience.
- SQL for querying and data extraction.
- Python or R exposure (beneficial).
- Industrial engineering tools (Lean, Six Sigma, mapping, optimisation).
Soft Skills
- Excellent communication and presentation skills.
- Ability to convert complex data into businessfriendly insights.
- Stakeholder engagement ability at operational and management level.
- High attention to detail and accuracy.
- Ability to manage multiple projects simultaneously.
Experience Requirements (2–5 Years)
- 2–5 years’ experience as a Data Analyst, BI Analyst, Process Analyst, or Industrial Engineer.
- Experience working with operational or supply chain data preferred.
- Demonstrated experience building dashboards and analytical reports.
- Exposure to process improvement or continuous improvement initiatives.
- Experience in manufacturing, logistics, operations, or service environments is advantageous.
6. Key Performance Indicators
- Accuracy, reliability, and quality of reports and insights.
- Improvement in operational KPIs due to analytical recommendations.
- Quality and adoption of dashboards and reporting tools.
- Successful execution of improvement projects.
- Stakeholder satisfaction and crossdepartment collaboration.
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