-Architected and implemented scalable API infrastructure for handling image generation requests using the SDXL model-Engineered Direct Preference Optimization (DPO) fine-tuning pipeline, enhancing model performance and output quality-Designed comprehensive Supabase database architecture including relational schemas for user management, image metadata, generation parameters, and usage analytics

-Engineered a Python-based data pipeline to analyze 10,000+ financial transactions, implementing advanced cleansing techniques and encoding management to deliver comprehensive insights across multiple time periods-Utilized Scikit-Learn and Prophet libraries to develop time series forecasting models, accurately predicting real estate purchase trends across diverse property types, resulting in a 15% increase in performance through data-driven investment strategies-Optimized web scraping processes using BeautifulSoup and regex to extract complex data structures from HTML and JavaScript, including Highcharts configurations, reducing manual data extraction time by 80%