· Created graphics for ORAI China’s daily articles, including cover and illustrations.· Designed posters and social media posts for weekly speaker and journal paper discussion events. · Re-designed the organization’s visual identity with a complete suite of logos, fonts, and cover.

· Automated the classification process of system defects. Developed a vector database to store defect information with Apache Spark and AWS. Implemented similarity search with multimodal large language models, achieving an 80% hit rate on ground truth data. Reduced engineering team’s manual work time by more than 50%, saving the company $100,000 annually.· Analyzed customer data using pandas and MySQL to validate customer ROI and construct business case. Designed data visualization using Matplotlib and Seaborn, facilitating two deals with Fortune 50 manufacturers.

· Leveraged PyTorch and Keras to build and train sales prediction models. Refined algorithm with LightGBM, XGBoost, and scikit-learn. Incorporated product images as a feature by employing Hugging Face to pre-train transformer models, improving prediction accuracy by more than 8.5% from purely textual predictions.· Developed a price optimization model using Gurobi and CPLEX. Reduced company cost by 10% and discount ratio by 50%, saving the company ̃$80000 annually.· Paper draft is being prepared for submission to Operations Research.

· Conducted time series analysis of sales data from offline and online retail channels using Python and PostgreSQL. Assessed the effectiveness of promotional campaigns during a major shopping festival. Generated comprehensive visual report using Power BI and Tableau.· Conducted A/B testing on the company’s dynamic pricing strategies. Identified key metrics and ran experiments using Optimizely. Leveraged Python (SciPy, NumPy) and R (t.test, prop.test) for statistical tests to validate feature performance.· Designed a sales data dashboard using Excel Scripts to reduce repetitive data cleansing tasks, saving the sales team $2,000 annually.

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