Lai Chun Kit

• Final-year Financial Mathematics student skilled in Python, R, and Power BI, with hands-on experience in predictive modeling and data visualization. Led a team to secure 3rd place in the RASIO 8.0 Data Science competition. Ready to apply my analytical skills to drive data-driven decisions.

• Aspiring data analyst with expertise in statistical analysis, machine learning (ARIMAX, LSTM), and dashboard creation. Proven track record in managing large datasets and delivering actionable insights under tight deadlines.

• Results-oriented student with a strong foundation in data analysis and visualization tools. Demonstrated leadership and technical skills through national-level data science competitions and academic projects.

• Proficient in Python, R, Power BI, and Excel, I specialize in analyzing datasets and developing data-driven solutions. My experience includes leading a team to create an award-winning economic dashboard.

• Dedicated data enthusiast with strong analytical and problem-solving skills. Experienced in building predictive models, creating dashboards, and presenting insights to diverse audiences. Excited to contribute to impactful data projects.

RASIO 8.0 Data Science Competition Third Place

• Using R, well constructed financial projections with a 95% accuracy rate in trend prediction for portfolio performance.
• Examined over 30 plus stock portfolios, applying statistical techniques to maximize allocation strategies, therefore increasing predicted returns by 15%.

• Designed and published Nomsim: Interest Rate Simulator, a Unity-based interactive and fun game simplified complex financial ideas for consumers.
• For two different game modes—mortgages and savings growth, implemented wide financial computation and real-time feedback mechanisms using C#.

• Created a C++ Monopoly simulation with additional gaming mechanisms, including property improvements, economic systems, and player movement using verified probability matrices.
• Developed an Inventory and Sales Management System in C++ that automated inventory tracking and profit reporting, reducing manual errors by 30%.

• Won 3rd place in the RASIO 8.0 Data Science Competition by constructing a predicted economic recovery dashboard in Power BI, combining machine learning models (ARIMAX, LSTM) for forecasting.
• Built interactive dashboards and visualizations in Power BI and Tableau, enhancing data accessibility for stakeholders.

• Applied advanced statistical approaches to evaluate forecasting models, offering actionable recommendations that better decision-making efficiency by 20%.
• Explored creative ways in R to test and analyze financial forecasting models, improving analytical accuracy.