2
Years of experience
4
years of post-secondary education
Work History
Financial Risk Strategy Intern
1 Month- Built a Power BI dashboard to monitor key post-delinquency metrics, including the resolution rate, for JD Baitiao accounts 1-6 months overdue.
- Investigated metric anomalies and trends across collection channels, identifying sources of performance fluctuations to support strategy adjustments.
- Supported A/B tests of collection strategies, including the design and evaluation of a penalty-interest waiver experiment. Helped launch one strategy and tracked post-launch metrics to inform further optimization.
Risk Modelling & Data Science Intern
3 Months- Led development of a domain-specific LLM (PyTorch, Hugging Face Transformers) to analyze how advertising channels affect content approval rates. Deployed it via Docker and a Flask API for internal decision support, identifying key patterns that boosted content approval efficiency by 15% and manual review effort by 20%.
- Applied econML's Causal Random Forest to evaluate how discount coupons influence user borrowing behavior. Validated the model's findings to refine marketing strategies, improving promotional targeting precision by 23%.
- Automated data pipeline on Alibaba Cloud ECS for daily risk model updates, ensuring models stayed up-to-date without manual intervention.
Full-Stack Developer Part Time
3 Months- Collaborated on developing a full-stack course enrollment platform (React/Next.js front end, Node.js/Express back end). Implemented secure user authentication flows and dynamic registration forms, with robust data handling and responsive design.
- Developed RESTful API endpoints for key features (user authentication, program enrollment, feedback submission, rewards notifications). Secured these endpoints with OAuth 2.0 and JWT (with refresh token rotation), integrating Google single sign-on to enhance user convenience and security.
- Optimized database interactions using Hibernate (JPA) for ORM, managing over 10GB of student and course data across PostgreSQL and Oracle. Improved data retrieval performance by 34% through query optimization and effective indexing.
Data Analysis Intern
2 Months- Processed and analyzed over 1 million data points from city-wide IoT sensors (e.g., traffic cameras, environmental monitors) using Python and SQL; Performed data cleaning and feature engineering to ensure data integrity for model training and performance analysis
- Developed and automated a suite of performance dashboards in Tableau to visualize key metrics like device uptime, data transmission latency, and anomaly rates
- Helped design and execute A/B tests for new firmware on smart traffic devices; Analyzed results using statistical methods to quantify a 12% improvement in pedestrian flow detection accuracy
Education
B.Sc. - Computer Science & Minor in Data Science
- Honors & Awards: Science Scholar (2023-2025), Dean's List (2023-2025), J. Fred Muir Memorial Scholarship, Charles & Jane Banks Scholarship, Go Global Exchange Award (Outstanding Exchange Student)
- Relevant Coursework: Data Structures & Algorithms, Software Engineering, Machine Learning, Database Systems, Simulation Methods for Optimization & Learning
- Involvement: Teaching Assistant & Lab Assistant, CS Dept.: Led tutorials and labs on DP algorithms, data structures, memory & CPU architecture, DBSM; mentored students in C++ programming and algorithmic problem solving.
- GPA: 3.91/4.0
Skills
Programming Languages: Python
C++
Java
JavaScript
TypeScript
SQL
R
Frameworks/Tools: React
Node.js
Express
Flask
Hibernate (JPA)
Prisma ORM
PostgreSQL
Oracle
Docker
Git
ML/DS: Scikit-learn
PyTorch
XGBoost
LangChain
econML
Pandas
NumPy
Prompt Engineering
Cloud & DevOps: AWS (EC2
S3
Lambda)
Alibaba Cloud
Jenkins
CI/CD pipelines
Websites
Projects
Project 1: Mass Spectrometry Background Modeling with Conditional VAE
- •Built a machine learning pipeline to model and remove background contamination from mass spectrometry data using a conditional variational autoencoder (CVAE).
- Implemented spectral preprocessing and feature engineering, including m/z binning, alignment, blank-profile construction, and baseline blank subtraction.
- Developed a dual-output neural architecture to jointly model background and sample-specific signals, with customized reconstruction and regularization objectives.
- Evaluated the system across 384 spectra and 29,729 features, achieving 0.9779 background-profile correlation and 99.9966% blank suppression.
Project 2: Scholar Forum: Academic Networking Platform
- Built a full-stack academic networking platform for publishing research articles, real-time search, and feedback
- Implemented the front end with React and JavaScript, Designed a PostgreSQL schema for user accounts, profiles, and comments
- Integrated AWS S3 (via AWS SDK) to store research documents, Deployed on AWS EC2 with Docker and Nginx for load balancing and scalability; supported 500 concurrent users in load testing.
Project 3: Investment Strategy Optimization Pipeline
- Built a Python-based command-line application for financial portfolio optimization, employing stochastic approximation algorithms to maximize the portfolio's Sharpe ratio (risk-adjusted return) while minimizing computational overhead.
- Collected and processed real-world financial datasets from three different companies using Pandas and NumPy. Developed simulation tests to validate the tool's performance under various market scenarios, ensuring the solution's reliability across different investment environments.
Timeline
Financial Risk Strategy Intern
JD.com, Inc.
09.2026 - CurrentRead More
Risk Modelling & Data Science Intern
DataPower International Technology Pte. Ltd.
05.2025 - 08.2025Read More
Full-Stack Developer Part Time
Mighty Moose Learning Centre, Ltd.
01.2025 - 04.2025Read More
Data Analysis Intern
Baidu PaddlePaddle (Guangzhou) AI Industrial Empowerment Center
06.2024 - 08.2024Read More
University of British Columbia
B.Sc. from Computer Science & Minor in Data Science
09.2022 - 05.2026Read More