Analytics & Modeling:
Understand business objectives Analyze supply chain challenges, define scope, and set success criteria.
Data feasibility assessment – Evaluate completeness, availability, and accuracy of supply chain data.
Data processing & cleansing – Handle missing data, outliers, and inconsistencies to ensure data integrity.
Exploratory analysis – Conduct exploratory data analysis (EDA) to uncover trends and root causes.
Develop & implement data science models – Apply descriptive, diagnostic, predictive and prescriptive analysis through statistical, optimization, or machine learning techniques to solve key supply chain problems.
Scenario planning & sensitivity analysis – Perform "What-If" analysis to evaluate business impact under different scenarios.
Independent problem-solver – Effectively executes tasks with minimal supervision while ensuring high productivity.
Manages moderately complex projects – Handles challenging but structured analytical problems, ensuring timely and impactful solutions.
Process Improvement:
Enhance modeling efficiency – Drive process automation,
identify opportunities to automate workflows and eliminate redundant tasks
Mentorship & validation – Guides analysts, reviews their work, and ensures analytical rigor in deliverables.
Minimum Qualifications
Bachelor’s degree from accredited university (Full Time) in Business Analytics or a related subject area
+3 years of related experience in Supply chain analytics
Solid analytic ability to translate business ask into mathematical model and ability to think “out of the box” & robust analytical skills.
Proficiency in Excel and PowerPoint, leveraging advanced functions for data analysis, visualization, and effective business storytelling
Preferred Qualifications
Post graduation in Industrial Engineering, statistics or Supply Chain operations
Qualified Certifications for supply chain and Data science
Learning Agility – driven by curiosity and a passion for continuous learning, always seeking to understand the "why" behind concepts