1. Migration of data processing code from SAS to PySpark.

Knowledge Base Chatbot:1. Deployed the ChatGLM2-6B model and collected both Traditional and Simplified Chinese Q&A datasets.2. Fine-tuned the model using P-TuningV2 to enhance performance.3. Built a knowledge base platform using LangChain and ChatGLM2-6B-int4, supporting document uploads.4. Used Django and FastAPI for frontend and backend management instead of Gradio.5. Applied custom prompt templates and text segmentation methods, testing the effects of LoRA and PtuningV2.6. Developed an internal, multi-device adaptive knowledge base platform.New Employee Handbook Editing Platform:1. Implemented the editing and updating features of a digital employee handbook using Summernote.2. Automatically identified Microsoft accounts based on user roles (HR or new employees), providing corresponding features such as the edit button or forwarding to supervisor option.3. Managed the frontend and backend systems using Django and FastAPI, with all pop-up windows defined by SweetAlert2.4. Integrated a chatbot powered by the Azure OpenAI GPT-4 model to provide intelligent Q&A for the latest version of the employee handbook

1. Maintained the code for generating daily trading signal reports based on stock price tick data, using T-SQL and Python, to assist the department in making trading decisions.2. Visualized the trading signal reports for specified products and developed a program to generate reports ready for direct output.3. Developed trading strategies using Multicharts, utilizing historical data for technical analysis. This process included defining entry logic, filters, and exit conditions (such as stop loss, take profit, and time-based exit), and performed backtesting with data from other years.