Discover companies you will love

Eugene Wee

Nanyang Technological University, Singapore / Bachelors of Computer Science

Eugene Wee

Nanyang Technological University, Singapore / Bachelors of Computer Science

Connect to learn more

You'll be able to see their introduction and other information once they have accepted your connection request.

Nanyang Technological University, Singapore4 years

Bachelors of Computer Science

-

McKinsey QuantumBlack x NTU Data Science Hackathon Dec 22 • Emerged as the winning team amongst 35 selected students, conducted prescriptive analytics regarding client’s customer churn, incorporated QB CausalNex library for model explainability and developed a Logistics Regression model to predict likelihood of churn with 96% accuracy.

  • NTU SCSE TechFest 2023 - Singtell!

    • Developed an end-to-end ML demand forecasting model for Singtel mobile phones inventory management using ARIMA and Exponential Smoothing curve to predict seasonal trends, created dashboard using Dash and hosted end-user web application using Heroku.

  • Hall Orientation Website

    NTU Hall of Residence 3 Orientation Full-stack Website (Dec 22 - Current) • Lead Developer in developing a full-stack website for Freshmen Orientation Camp using React.JS with Tailwind CSS, crafted UI/ UX wireframe using Figma and hosted on Firebase. Implemented backend interactions utilising Firestore and User Authentication.

  • The Green World Project

    - Spearheaded team of 4 in performing database modelling and design for both relational (mySQL) and non-relational (noSQL) databases using publicly-scraped environmental data. - Developed succinct queries with DDL & DML commands for data extraction and curated data visualisations using R to highlight urgent environmental issues and effects of climate change.

    -
  • Identifying Phishing URLs using ML Paradigms (Distinction)

    • Coordinated team of 3 in building and fine-tuning classification machine learning models to detect phishing URLs, achieved a high model accuracy of 95.28% from model ensembling (Logistics Regression, Decision Tree & Random Forest) • Incorporated key ML techniques, Principal Component Analysis for data mining, GridSearchCV for model fine-tuning and Ensembling for enhancing model performance.

    -

OCBC Bank4 months

STEM@OCBC Intern

-

• Conducted prescriptive analytics for project management and received commendations for actionable insights with proposed performance metrics for stakeholder reporting. • Curated dashboards using Jupyter Notebook and documented analytical findings in Confluence.


Receive Scouts from companies