Hi, I’m Ke Gong, a data-driven software engineer with a passion for turning messy data into actionable insights. I enjoy building scalable data pipelines, analytics dashboards, and AI-powered tools that improve decision making and efficiency. I’m currently pursuing a Master of Science in Mathematics at Nipissing University and hold a Bachelor of Science in Computer Science from the University of Toronto. I thrive in cross-functional teams and love delivering practical solutions that combine mathematical rigor with software engineering best practices.

Ke Gong

Hi, I’m Ke Gong, a data-driven software engineer with a passion for turning messy data into actionable insights. I enjoy building scalable data pipelines, analytics dashboards, and AI-powered tools that improve decision making and efficiency. I’m currently pursuing a Master of Science in Mathematics at Nipissing University and hold a Bachelor of Science in Computer Science from the University of Toronto. I thrive in cross-functional teams and love delivering practical solutions that combine mathematical rigor with software engineering best practices.

Available to hire

Hi, I’m Ke Gong, a data-driven software engineer with a passion for turning messy data into actionable insights. I enjoy building scalable data pipelines, analytics dashboards, and AI-powered tools that improve decision making and efficiency.

I’m currently pursuing a Master of Science in Mathematics at Nipissing University and hold a Bachelor of Science in Computer Science from the University of Toronto. I thrive in cross-functional teams and love delivering practical solutions that combine mathematical rigor with software engineering best practices.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
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Work Experience

Machine Learning Intern at Convoloo
June 1, 2025 - September 8, 2025
Preprocessed a clinical dataset of ~10,000 records to support treatment outcome prediction using machine learning. Developed a modular pipeline to handle semantic missing values and encode categorical features using domain-specific mappings, enhancing feature granularity and model interpretability. Computed and visualized multivariate correlations (Cramér’s V for categorical and Pearson for numerical) using heatmaps to guide feature selection, reduce data leakage, and improve model transparency. Built modular scikit-learn pipelines and benchmarked 12 classifiers (Logistic Regression, Random Forest, XGBoost), achieving 86% accuracy with the top-performing model.
AI Developer Intern at Climind
August 1, 2024 - September 8, 2025
Designed and deployed a real-time rPPG pipeline using OpenCV, Dlib, and Scikit-learn, achieving 92%+ heart-rate accuracy. Optimized face detection and signal extraction to reduce edge deployment latency by 30%. Deployed a Phi-3-Mini LLM with vLLM on AWS EC2, cutting response times to under 150 ms. Benchmarked multiple LLMs in a small team, improving healthcare prompt coherence by ~20%.
Data Engineer Intern at iDriveCareer Consulting Ltd
October 1, 2023 - September 8, 2025
Implemented a Python-based web scraper to harvest 10,000+ pricing records, reducing manual data collection effort by 95%. Built automated data pipelines with SQL Server integration to boost throughput by 25%. Performed data cleaning and transformation to ensure 99.5% data integrity for analytics. Conducted exploratory data analysis and clustering to identify pricing anomalies, contributing to a 12% improvement in competitiveness. Created dashboards in Power BI and Matplotlib to inform pricing decisions and support conversions.

Education

Master of Science in Mathematics at Nipissing University
September 1, 2024 - June 1, 2026
Bachelor of Science in Computer Science at University of Toronto
September 1, 2020 - June 1, 2024

Qualifications

Add your qualifications or awards here.

Industry Experience

Software & Internet, Healthcare, Professional Services, Education