Donna Bui

• Performed data collection, cleaning, preparation and validation to support high-quality data and catch errors before processing.
• Conducted statistical analysis: Using linear regression statistical model to identify industrial patterns and trends.
• Communicated with senior game designers/ mathematicians to propose new game concepts based on emerging trends.
• Conceptualized and create game mathematical packages using Excel.
• Verified game math through proofs and/or simulations using Visual studio code, R programming or Python programming languages.
• Performed peer review of models formulated by other game designers/ mathematicians and evaluate credibility.

• Assisted supervisor in development of project plans and timelines.
• Gathered, documented, and modeled data to assess business trends.
• Developed compelling presentation decks to gain approval for ideas and communicate results
• Produced detailed and relevant reports for use in marketing business product.
• Collaborated with fellow interns to conduct market and competitor research and collectively crafted comprehensive presentation.
• Monitored market trends and competitor activities to identify areas of potential opportunity.

• Handled customer inquiries and suggestions courteously and professionally.
• Built relationships with customers to encourage repeat business.
• Answered multi-line phone system, routing calls, delivering messages to staff and greeting visitors.
• Restocked supplies and placed purchase orders to maintain adequate stock levels.
• Operated cash register for cash, check, and credit card transactions with excellent accuracy levels.
• Enhanced sales by 10% boost through strategic introduction of on-demand product line into store.

Australian Actuaries Institute

Foundation Program exemption:

• CS1 - Actuarial Statistics 1
• CS2 -Risk Modeling and Survival Analysis
• CM1 -Actuarial Mathematics 1
• CM2 -Financial Engineering and Loss Reserving
• CB1 -Business Finance
• CB2 -Business Economics

Actuarial Modeling Project - Grade 85/100

• Actuarial Modeling for an insurance company's new product. (Using R programming)
• Examining and employing a variety of exposed-to-risk and mortality projection techniques.
• Visualizing and analyzing historical data.
• Applying parametric modeling to fit the model with historical data, calibrating parameters, validating hyper-parameters, testing the goodness of fit of the model using out-of-sample data.
• Reporting the Mean Square Error to test the good fitting of the model.
• Modeling and projecting potential estimations for data, visualizing, and analyzing projected data.
• Discussing limits and proposing improvements for data projection.