As a Data Science Intern at Systems Ltd, I played a key role in developing advanced AI and machine learning models. Additionally, I provided consultation services to K-Electric's data science department, contributing to their data-driven decision-making processes and operational efficiency.- Automated Technical Documentation Generation using Retrieval-Augmented Generation (RAG) Pipeline: Integrated LangChain, OpenAI GPT-4 API, OpenAI embeddings, and FAISS vector indexing to create a… Show more As a Data Science Intern at Systems Ltd, I played a key role in developing advanced AI and machine learning models. Additionally, I provided consultation services to K-Electric's data science department, contributing to their data-driven decision-making processes and operational efficiency.- Automated Technical Documentation Generation using Retrieval-Augmented Generation (RAG) Pipeline: Integrated LangChain, OpenAI GPT-4 API, OpenAI embeddings, and FAISS vector indexing to create a robust RAG pipeline, enhancing data retrieval and analysis. Utilized Hypothetical Document Embeddings (HyDE) to improve recall by 25%, ensuring more comprehensive data retrieval and analysis. Leveraged the RAG pipeline to automate the creation of detailed technical proposals, increasing Pre-Sales Department efficiency by 60%.- Anti-Money Laundering Predictive Model: Designed and implemented a predictive model using K-Means clustering to detect unusual transaction patterns, facilitating real-time monitoring and dynamic visualizations for AML compliance.- Supply Chain Default Prediction Model: Developed predictive models using CatBoost and XGBoost to forecast potential default risks in the supply chain, enhancing decision-making and risk management processes.- Consulted for K-Electric's Data Science Department: Advised on implementing a GPT-4 powered RAG system with text-to-speech capabilities. This system enabled mechanics to access repair information in real-time, reducing the need for helpline support and improving repair efficiency. Show less

During my internship at HBL, I contributed to multiple data-driven projects, developing innovative tools and models that enhanced the bank's operational efficiency and strategic capabilities.- Branch Locator Dashboard: Identified a need for a streamlined process to locate bank branches and took the initiative to develop a scalable Branch Locator Dashboard. I utilized web scraping tools to scrape data (Selenium, Beautiful Soup), processed the data (Pandas), and created an interactive map… Show more During my internship at HBL, I contributed to multiple data-driven projects, developing innovative tools and models that enhanced the bank's operational efficiency and strategic capabilities.- Branch Locator Dashboard: Identified a need for a streamlined process to locate bank branches and took the initiative to develop a scalable Branch Locator Dashboard. I utilized web scraping tools to scrape data (Selenium, Beautiful Soup), processed the data (Pandas), and created an interactive map dashboard (Dash, Plotly). The tool delivers real-time, accurate branch information, and includes an interactive feature that offers a competitor analysis upon selecting a location on the map. It serves as a strategic resource, enhancing understanding of the competitive landscape in real-time.- Multi-class Classification Model: Successfully implemented and trained a multiclass risk level classification deep learning model using PyTorch, an achievement made possible by leveraging a feedback network architecture.- RPA Department Assistance: Gained significant skills in RPA (Robotic Process Automation) through active participation in departmental projects and learning from experienced staff members. This hands-on experience facilitated my valuable contribution to the successful operation of the RPA department.- MLOps Documentation: Authored comprehensive documentation outlining MLOps processes, which served as a significant resource for the bank. The guidelines and best practices provided in this documentation contributed to improving the deployment, monitoring, and maintenance of machine learning models within the bank. Show less