Lefei (Raina) Hong

Early-career data analyst with expertise in finance and computer science, currently pursuing a master's degree in computer science specializing in data science and AI. Proficient in SQL, Python, and data visualization tools to analyze financial and operational data, develop dashboards, and support business decision-making. Demonstrated ability to translate complex data into actionable insights through performance reporting and analysis.

Principles of Data Science | Used Car Price Analysis

• Conducted end-to-end analysis on a used car dataset with 18,000+ records, cleaning and transforming raw data into a structured dataset with 14,000+ usable records.
• Performed exploratory data analysis to identify key price drivers, including vehicle age, mileage, and fuel type.
• Built and compared regression models to evaluate predictive performance, with Random Forest achieving the best result (R² = 0.878), and translated findings into practical pricing insights.

Database Management Systems | Relational Database System Project

• Designed a normalised PostgreSQL database schema to manage inventory, transaction, and financing data in a structured relational system.
• Developed SQL queries and backend integration to support multi-criteria data retrieval, analysis, and reporting.
• Implemented validation rules, integrity constraints, and stored procedures to improve data accuracy, efficiency, and reliability.

Machine Learning & Data Mining | Predictive Data Analysis Project

• Developed an end-to-end data analysis pipeline for structured and image data, including preprocessing, cleaning, and normalisation.
• Compared multiple analytical approaches and applied cross-validation to evaluate model performance and improve result reliability.
• Interpreted model outputs and translated findings into data-driven insights to support predictive analysis and decision-making.

Fuzhou University, School of Finance, China

Teaching Assistant / Department Head Assistant | Jun 2021 – Jun 2024

• Supported faculty research by collecting, cleaning, and organising datasets using Excel and SQL, improving data quality and readiness for analysis.
• Coordinated communication between students, faculty, and administration, translating requirements into structured documentation and progress tracking.
• Consolidated data from multiple sources and prepared research materials and reports using Excel, ensuring consistency, accuracy, and clarity.

• First Prize – Cross-Strait, Hong Kong & Macau University Students Vocational Skills Competition (Financial Quantitative Investment Trading), 2022
• Third Prize (National Finals) – Financial Innovation Competition, Bank Core Business Professional Competency, 2022
• Third Prize – 10th National Securities Investment Simulation Training Competition, 2023

• Hong, Lefei (First Author) Financial Market Reactions under the Russia–Ukraine Conflict: An Empirical Study Based on a Multi-factor Model. Proceedings of the 2nd International Conference on Business and Policy Studies (CONF-BPS).
• Conducted empirical analysis of financial market behaviour using a multi-factor model, demonstrating quantitative research and data interpretation skills.