I am a data science student with practical experience in Python, R, SQL, and core machine learning techniques. I have built end-to-end projects focusing on data preprocessing, statistical modelling, and constructing classification and regression pipelines. I am a bilingual communicator who thrives in fast-paced, multicultural environments and am motivated by applying data to drive evidence-based decisions. I enjoy solving problems, learning new tools quickly, and communicating technical insights clearly to stakeholders.

Zongye Lyu

I am a data science student with practical experience in Python, R, SQL, and core machine learning techniques. I have built end-to-end projects focusing on data preprocessing, statistical modelling, and constructing classification and regression pipelines. I am a bilingual communicator who thrives in fast-paced, multicultural environments and am motivated by applying data to drive evidence-based decisions. I enjoy solving problems, learning new tools quickly, and communicating technical insights clearly to stakeholders.

Available to hire

I am a data science student with practical experience in Python, R, SQL, and core machine learning techniques. I have built end-to-end projects focusing on data preprocessing, statistical modelling, and constructing classification and regression pipelines.

I am a bilingual communicator who thrives in fast-paced, multicultural environments and am motivated by applying data to drive evidence-based decisions. I enjoy solving problems, learning new tools quickly, and communicating technical insights clearly to stakeholders.

See more

Experience Level

Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate

Language

English
Fluent
Chinese
Fluent

Work Experience

Team Leader & Lead Data Scientist at BNPL Fraud Risk Analysis – Applied Data Science Project
August 1, 2025 - November 1, 2025
Led a 4-member team to develop a fraud-risk prediction and merchant trustworthiness system using a 510,000-row BNPL dataset, managing task allocation, code review, and integration. Built and optimized Lasso, Random Forest, and XGBoost models with feature engineering, hyperparameter tuning, and cross-validation; achieved R² = 0.915, 0.997, 0.982. Designed merchant risk scoring framework by weighting behavioral/transactional features, and produced top-10 and top-100 ranking outputs for merchant risk assessment. Conducted merchant analytics and created visualisations (revenue-risk correlation, fraud distribution, category performance), generating insights for identifying high-risk merchants. Explained key predictive features (e.g., avg_fraud_probability) and business implications in final presentation. Oversaw project workflow, debugging, codebase consistency, and coordinated with instructors to ensure timely delivery and alignment with learning objectives.

Education

Bachelor of Science at The University of Melbourne
February 1, 2023 - November 1, 2025

Qualifications

Add your qualifications or awards here.

Industry Experience

Software & Internet, Financial Services, Education, Professional Services, Media & Entertainment