Conducted a research project for analytics and marketing products (CDP, AB Test) in the pan-internet industry;Combined product competitive landscape research with customer demand research to identify industry segmentation directions and issued a report guiding the future industry track of the analytics and marketing products;Formulated market research and customer interviews for RTA (Real-Time-API) products, participated in the development of product pricing standards using gradient pricing model, and ensured daily data updating in the POC phase;Collaborated with product architects to integrate Cloud Knowledge content library, including updating and improving the page layout using visual UI tools; Consolidated product resources, resulting in over 10% improvement in the efficiency of the product architects' work;

Researched hydrogen refueling station construction conditions and aided conduct cost structure analysis including defining cost elements, obtaining cost data and establishing a cost model utilizing Wind database, financial reports and GPT, leading to a strategic cooperation agreement with HYDREXIA Energy in the end;

Contributed to ZTE Corporation Financial Report Evaluation Program, conducted research on suppliers of telecommunications equipment and analyzed fraud motives based on its business management, judicial supervision, and key information found in financial reports;Initiated research of the stock price level with the analysis involving price-to-book and price-to-sales ratios and established prediction model with recall and accuracy higher than 70% utilizing ARIMA and LSTM;

Implemented a market analysis on electric automobile industry, including analyzing user profile data, regional economic data from Oxford Economies and GM internal databases and utilizing machine learning algorithms like Kmeans clustering, decision trees, and linear fitting to verify market segmentation;Developed Python programs for database field matching, integrating market and vehicle manufacturing data. leading to a time efficiency improvement of over 20% compared to manually calling related database data;

Promoted low-code development of SAP data process automation, utilizing Power Automate to achieve daily automatic update of company's inventory-related data, saving over 30% of time cost for data update;Compiled office automation programs to integrate massive financial data files, using Python (xlwings, pandas) for fieldmatching of 100,000 level financial Excel reports, saving over 50% of data processing time;Involved in inventory optimization project with budget of several hundred million, using Anylogic intelligent modeling to simulate inventory and turnover process of factory, identifying bottlenecks in inventory transit and assisting in reducing inventory level to less than one billion;