l Research and analyze existing national trends within youth sports by evaluating the quality of market and competitor data reporting l Complete sports index research projects, ensuring applicability to the amateur and youth sports marketplace Communicate with various partners in various sports related initiatives and support web developers to optimize visualization with Power BI

l Applied discounted cash flow model in Bloomberg to analyze and predict future returns on earnings of target companies, pricing for them based on valuation method and applied Monte Carlo to do risk modeling on VaR(value at risk) to assist in-depth valuation. l Collected information on Wind and processed marketing data for quantitative analysis on real estate companies to assist analyst for organizing research summary and conducting causal inference and regression to draft in-depth reports. l Conducted investment meeting slides and prepared road show materials for institution clients to make better portfolio management. l Presented marketing strategy analysis, policy analysis and risk analysis at monthly meeting to analysts and managers.

l Processed competitive analysis for an AI wealth management product and promoted it as a value add for clients by organizing roadshow events with the support of Legal department; Topped internal sales competition. l Assisted organize training events for branch managers by teaching product knowledge, providing market commentary, and macro-economic trends. Created promotion video through social media, Wechat, Weibo and Tiktok to make online instruction and invitation available. l Applied MySQL to streamline the team’s operational tasks such as keeping track with institution clients on their subscription of fund products and create checklist for gifts on different membership clients on special days to Sales department for better operation. l Classify based on clients’ behavior and risk preference features through Python and categorizing clients’ information into the database. l Performed quantitative calculation such as NAV of funds and handled redemption orders and customer database.

l Assisted surveys design in demographic and basic financial situation data collection to study the income of families in the program l Applied MySQL to assist data cleaning, delete and add terms to the dataset for further analysis. l Retrieved Poverty-stricken data of 15 counties online with Python, set subsistence as control group to predict effect of the different sources of income, the amount of government subsidies and per capital living expenditure to their total income l Analyzed and ranked the money use efficiency of 72,000 families in the program, plotted in **Tableau** as bubble shape and generated investigation reports to show the effects of this program on people’s enthusiasm towards work to stakeholders.

l Promoted loan products for individual and small private business district and study their behaviors and demands to strengthen marketing strategy to improve promotion efficiency. l Applied Python to gather merchants’ basic information based on IT department’s support and assisted on creating credit model and causal inference analysis to evaluate clients’ max loan amount. l Cross-team collaboration and assisted in external negotiation with third party to acquired clients’ data and enrich database for ab testing.