• Developed and implemented a Python-based web crawler to efficiently extract and compile data for over 30,000+ projects, establishing a comprehensive crowdfunding research database• Leveraged Excel VBA and Power Query to enhance data organization and analysis for crowdfunding research

• Conducted a detailed review of insurance policies using Excel, identifying inconsistencies in premiums and ensuring data accuracy• Employed statistical analysis techniques to build robust linear regression models, playing a key role in establishing composite rates for underwriter utilization• Determined new rate adequacy by aligning size factors and cross-referencing multiple tables with distinct criteria

• Evaluated historical labor claims and insurance data to provide guidance to the government around building sufficient funding for future claims• Analyzed 10 million rows of insurance policy and historical claims data and led efforts to organize data based on relevant attributes into cross-analyze tables using Access• Calculated five types of incidence rates (retirement rate, birth rate, injury or sickness rate, permanent disability rate, and death rate) in Excel, providing a foundation for actuarial assumptions