Hi, I'm Biyan Huang (known as Yanness online), a passionate software developer and data scientist based in Markham, ON, Canada. Currently pursuing a Bachelor's in Applied Science at York University, I have a strong foundation in full-stack development, data analysis, and machine learning. With hands-on experience from internships at IBM and Scotiabank, I enjoy building scalable applications, deriving insights from data, and solving real-world problems through code.

• Email: yannesswong0918@gmail.com
• GitHub: yanness168 (32 public repositories)
• LinkedIn: Yanness Huang
• Location: Markham, ON
• Skills Badges:

Bachelor of Applied Science
September 2024 – Present
Markham, ON

• Relevant Courses: Introduction to Computational Problem Solving, Object-Oriented Problem Solving, Web Development Basics

College Diploma in Computer Programming
September 2021 – December 2023
Etobicoke, ON

• Cumulative GPA: 91% (4.0)
• Honors: Dean’s Honor List
• Relevant Courses: Web Application Development (Java, Spring Boot), Advanced Database Programming (PL/SQL, Python), Application Testing (JUnit, Python Unittest), Networking & Telecommunication, Modern Web Technologies (Express.js, Node.js)

Back-end Developer Intern
September 2024 – Present
Markham, ON

• Developed FVT and unit tests for inference proxy using Golang, ensuring high reliability, security, and compliance.
• Led the Batch Inferencing project, designing and implementing new APIs to optimize model inference workflows.
• Collaborated with cross-functional teams to integrate and deploy microservices on the Watsonx platform using Jenkins, Kubernetes, and Docker, improving service delivery efficiency.
• Contributed to code reviews and implemented best practices through GitHub, enhancing maintainability and quality.

Data Scientist Intern
September 2023 – April 2024
Toronto, ON

• Conducted in-depth industry analysis for Customer Lifetime Value using Python and SQL, identifying key seasonality in revenue behaviors and enhancing time series model precision by 18% using coefficient of variance, ACF/PACF plots, and time series clustering.
• Developed two robust versions of Revenue Segmentation model – Individual & Linked – and performed stability tests (PSI) by scoring two consecutive years of data, ensuring model stability with less than 5% deviation.
• Mastered diverse time series forecasting methodologies, establishing robust baseline models (Naive Forecast, MA, WMA). Elevated model performance by 27% by deploying advanced benchmark models (ARIMA, SARIMA, and SARIMAX).
• Designed a "Factbook" Power BI dashboard for commercial customers and automated it using PySpark and Airflow.

Data Scientist Intern
January 2023 – April 2023
Toronto, ON

• Spearheaded classifier and clustering models to predict revenue direction and value level, contributing to the foundation of Customer Lifetime Value – Revenue Segmentation.
• Performed multi-step data preprocessing on 1,000,000+ rows of data and engineered features using business logic to improve model performance. Utilized Python to develop robust baseline models (Random Forest, LGBM, and XGBoost) as benchmarks.
• Employed hyperparameter tuning techniques (Optuna, Grid Search) to enhance model accuracy by 23% F1-score on the classifier and integrated classifier outputs into clustering for improved revenue segmentation prediction.
• Effectively communicated complex data insights to stakeholders, collaborated with team members to refine model metrics, and presented findings to both technical and business audiences, driving CLV development with a 200% increase in stakeholder engagement.

• Data Analytics Certificate – Google
• Data Analysis with Python Certificate – IBM
• Preparing for Google Cloud Certification: Cloud Engineer – Google

Explore my GitHub for personal projects, including web apps, data analysis tools, and ML models. Notable contributions include collaborative work on platforms like OpenBid (map-first bidding marketplace) and various open-source experiments in backend development and data pipelines.

Feel free to reach out for collaborations, mentorship, or discussions on software engineering, data science, or cloud technologies!