Ng Wee Chai

Data Analyst | Data Scientist

Ng Wee Chai Profile Picture

I’m a results-driven Data Analyst and aspiring Data Scientist, transitioning from architecture into business intelligence. I use Python, SQL, Power BI, and machine learning to extract insights and build dashboards that drive strategic decisions. My work focuses on sales forecasting, HR analytics, and customer segmentation, with a passion for solving real-world business problems through data. I’m committed to continuous learning and growth, actively pursuing advanced certifications to deepen my impact in the data science field.

Contact Me:
+65 9733 1257
weechai88@gmail.com

Professional Projects

Project 01: Cafe Sales Dashboard & Insights

HR Dashboard

This dashboard was built for a cafe business to uncover sales performance trends, customer behavior, and operational opportunities. Developed during a freelance project (with anonymized data), it enables stakeholders to monitor key metrics, optimize strategies, and make data-driven decisions with confidence.

  • Cleaned and transformed raw sales data using Python, including feature engineering (e.g., TotalPrice).
  • Segmented customers with RFM analysis to identify loyal and churned groups for targeted campaigns.
  • Built a heatmap to visualize hourly sales patterns and recommend staffing adjustments.
  • Highlighted revenue trends, top-selling products, and customer loyalty behavior.
  • Tracked performance with dynamic KPIs, including a 20.26% sales increase from Oct to Dec 2024.
  • Tools Used: Power BI, DAX, Python (pandas), Excel

Project 02: E-Commerce Sales Analysis

E-Commerce Output 1

This Python-driven exploratory data analysis project investigates sales trends and customer behavior for an e-commerce retailer. It was designed to demonstrate how raw transaction data can be transformed into meaningful business insights using only Python libraries, without relying on external BI tools.

  • Processed over 500,000 transaction rows using pandas, with cleaning, aggregation, and feature engineering.
  • Performed RFM analysis and custom churn logic to identify inactive customers.
  • Visualized monthly sales trends using bar and line charts for seasonality analysis.
  • Ranked top 5 products and top countries by total revenue using horizontal bar charts.
  • Plotted churned customer distribution using Seaborn histograms.
  • Tools Used:Python, pandas, Matplotlib, Seaborn, Jupyter Notebook

Project 03: HR Analytics for Interior Design

HR Dashboard

This Power BI dashboard was developed for a small interior design firm to visualize and monitor key HR metrics across a multi-year period (2021–2025). The goal was to provide stakeholders with a centralized view of workforce composition, employee well-being, and organizational growth, all while supporting HR decisions around staffing and budgeting. Due to confidentiality, the dataset has been modified while retaining real-world structure and logic.

  • Created interactive KPI cards to track headcount, salary averages, and leave balances.
  • Designed charts for team composition, gender and age distribution, and role hierarchy.
  • Incorporated attrition analysis and historical staff growth trends.
  • Highlighted key metrics like employees with high leave balances and salary-to-qualification correlation.
  • Tools Used: Excel (data preparation), Power BI (DAX, visuals, and dashboard design)

Personal Projects

Project 1: Backpacker Travel Planning App

  • Designed an AI-powered chatbot that personalizes travel experiences for backpackers visiting Singapore.
  • Features:
    • Integration with Google Sheets for real-time itinerary planning.
    • Enhanced user interaction through OpenAI API for natural language processing.
    • Seamless navigation with Google Maps API for visualizing itineraries and locations.
    • Supports both solo and group planning, catering to various travel styles.
  • Tools & Technologies:
    • Python: Machine learning model to improve response accuracy by leveraging RAGAS score analysis.
    • OpenAI API: For dynamic and conversational user interactions.
    • Google API Suite: For Sheets and Maps integration.

Project 2: HDB Price Prediction

  • Developed a machine learning model to predict Housing and Development Board (HDB) resale prices in Singapore.
  • Features:
    • Conducted extensive data cleaning, feature engineering, and exploratory data analysis (EDA).
    • Implemented advanced regression models like XGBoost, LightGBM, and CatBoost for accurate predictions.
    • Created a Streamlit app allowing users to input property details and get real-time price predictions.
  • Tools & Technologies:
    • Python: Utilized pandas, numpy, and scikit-learn for data preprocessing and modeling.
    • Machine Learning Models: Evaluated and fine-tuned models using RMSE and R² metrics.
    • Streamlit: Built and deployed a user-friendly application for price prediction.

Project 3: Christmas Gift Exchange

  • Designed a festive app to simplify Christmas gift exchanges by automating the draw process.
  • Features:
    • Ensured fair gift allocation by preventing participants from being assigned to themselves.
    • Provided an intuitive interface for adding, viewing, and managing participant lists.
    • Included a real-time draw functionality to display gift pairings instantly.
    • Added festive elements like autoplaying Christmas music for an engaging user experience.
  • Tools & Technologies:
    • Python: Implemented the logic for fair gift distribution using randomization.
    • Streamlit: Built an interactive, web-based app for user-friendly interactions.
    • HTML & CSS: Enhanced the app with embedded audio for a festive ambiance.

Project 4: Mapping EV Charging Stations

  • Designed an interactive map showcasing electric vehicle (EV) charging Stations.
  • Features:
    • Extracted geocoordinates from CSV data for precise mapping.
    • Visualized data with Folium, incorporating marker clusters for better interactivity.
    • Created pop-ups displaying station names for an enhanced user experience.
  • Tools & Technologies:
    • Python: Processed CSV data and geocoordinates for visualization.
    • Folium: Built an interactive map with FastMarkerCluster for efficient data representation.

Project 5: Scraping Nike Product Data

  • Extracted and visualized product details from Nike's website for portfolio showcase.
  • Features:
    • Automated data extraction of product names, prices, and color options using Python.
    • Implemented pagination handling and scrolling with Selenium to gather complete product data.
    • Generated a structured dataset for potential business analysis or inventory management.
  • Tools & Technologies:
    • Python: Used BeautifulSoup and Selenium for web scraping and automation.
    • Pandas: Processed and structured data into a CSV and Excel format for further analysis.
    • Folium: Explored data visualization techniques for geographic representation of product availability.

Project 6: Visualizing Singapore Visitor Trends

  • Developed an interactive Tableau dashboard to analyze and showcase Singapore's visitor statistics.
  • Features:
    • Explored trends in visitor demographics, arrival patterns, and top destinations.
    • Created interactive filters for a user-friendly data exploration experience.
    • Highlighted seasonal and regional variations in visitor data.
  • Tools & Technologies:
    • Tableau: Designed and published an interactive dashboard for visual insights.
    • Data Cleaning: Processed raw visitor data to ensure accuracy in visualization.

Contact Me

Feel free to reach out via phone, email, or connect with me on social media!

Phone: +65 9733 1257
Email: weechai88@gmail.com

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