Edward Lim | About Me
Edward Lim
Data Science and Analytics
I work at the intersection of business operations, data science, and decision support. My background spans APAC e-commerce, service cost forecasting, inventory analytics, and reporting automation, with hands-on experience turning messy business questions into reliable datasets and practical recommendations.
I am currently pursuing the Master of IT in Business at Singapore Management University, specializing in Data Science and Analytics. This portfolio brings together the work I am building across forecasting, machine learning, visual analytics, and applied business problem solving.
Focus Forecasting, machine learning, and visual analytics
Program SMU MITB Data Science & Analytics
Experience HARMAN, Sony Electronics, and HPE
Experience
Data Analytics Specialist, Digital and E-Commerce - APAC
HARMAN International
- Built real-time JBL eShop reporting for campaign tracking and APAC market performance reviews.
- Consolidated distributor sales, campaign, and category data into a cleaner regional reporting structure, reducing manual reconciliation by 80%.
- Automated recurring Excel reporting from multiple flat-file sources, cutting preparation time by at least 70%.
- Analyzed e-commerce and paid media data across TikTok, Shopee, Lazada, Tokopedia, Amazon, CPAS, and Meta for QBR discussions.
Business Data Analyst - APAC
Sony Electronics South East Asia Pacific
- Supported APAC budgeting and repair cost provisions through forecasting, risk analysis, and market-level business context.
- Investigated historical and forecasted service cost data to identify anomalies, gaps, and key cost drivers.
- Worked with cross-functional teams to define forecasting assumptions and evaluate market scenarios.
- Automated multi-country forecast consolidation with Excel VBA for faster regional reporting.
Business Operations Analyst
Hewlett Packard Enterprise
- Analyzed inventory and asset lifecycle data, helping finance mitigate losses by approximately $200K USD per quarter.
- Evaluated defective product return strategies, reducing spare parts asset devaluation by 10% and lowering freight costs.
- Built Power BI dashboards for inventory monitoring and excess stock identification.
- Automated reporting workflows with Excel VBA, reducing manual effort by approximately 60%.
Business Application Support Consultant
MicroChannel Singapore Pte Ltd
- Resolved SAP Business One system and data issues across finance and sales modules.
- Translated business requirements into proof-of-concept system improvements.
Education
Singapore Management University
Master of IT in Business
Data Science and Analytics Track
Aug 2025 - Dec 2026
University of London (SIM)
Bachelor of Science in Business and Management
Second-Upper Class Division
Aug 2014 - Aug 2017
Selected Projects
Demand Forecasting
Inventory Optimization
Demand Forecasting and Inventory Optimization
Topics: Python, Elastic Net, Random Forest, LightGBM, Prophet, SKU Prioritization
Forecasted Walmart POS demand and translated model outputs into inventory planning decisions using sliding-window validation and capacity-constrained SKU prioritization.
Multi-Label Image
Classification
Multi-Label Image Classification
Topics: TensorFlow, Deep Learning, Computer Vision, Multi-Label Classification
Built a deep learning workflow for image attribute prediction, with evaluation across label-level metrics, threshold review, and error analysis.
Transport Data
Architecture
Unified Transport and Ridership Analytics Architecture
Topics: Big Data Architecture, Spark, Airflow, HDFS, Hive, Trino, Superset
Designed a hybrid analytics architecture for transport operations, covering ingestion, batch processing, predictive maintenance, ridership analytics, and reporting.
Shiny Visual
Analytics App
Shiny Visual Analytics Application
Topics: R Shiny, Quarto, EDA, Customer Segmentation, Predictive Modeling
Built a fintech customer behavior app that combines exploratory analysis, clustering, and predictive modeling for customer value analysis.
Bank Default
Prediction
Bank Default Prediction
Topics: PySpark, Medallion Architecture, XGBoost, Logistic Regression, Model Monitoring
Designed a bank default prediction pipeline with feature stores, chronological validation, model governance, drift monitoring, and a Streamlit control dashboard.
Delivery Delay
Risk Prediction
E-Commerce Delivery Delay Risk Prediction
Topics: Airflow, MLflow, XGBoost, Random Forest, Logistic Regression, Evidently, Streamlit
Operationalized late-delivery risk prediction for Olist e-commerce orders with batch inference, monitoring, retraining triggers, and a fulfillment dashboard.
Skills
Programming and Query
Python, SQL/MySQL, R
Data Science and ML
Pandas, NumPy, Scikit-learn, TensorFlow, XGBoost, LightGBM, Random Forest, Elastic Net, K-means Clustering, Time Series Forecasting
Data Engineering and MLOps
PySpark, Airflow, MLflow, Docker, Git
Data Analysis and BI
Excel VBA, SAS Viya, Power BI, Tableau, Looker Studio, Streamlit
Certifications and Languages
Certification: SAP Business One, SAP Certified Application Associate
Languages: English, Mandarin
Beyond Analytics
Outside of analytics, I enjoy coffee brewing, playing piano, singing and taking long walks with my dog, Leelo. These routines keep me grounded and curious, and they reflect how I like to approach analytical work too: patiently, observantly, and with attention to the details that are easy to miss.
Leelo, my weekend analysis partner