Muhammad Ahmed

FinTech-focused Business Data Analytics undergraduate (COMSATS University Islamabad) with hands-on experience building end-to-end data science solutions churn prediction, propensity modeling, NLP/RAG chatbots, and deep learning sentiment models deployed as interactive Streamlit applications. Proficient in Python, SQL, and BI tools (Power BI, Tableau, Excel), with a strong grounding in financial statement analysis.

Data Science Intern, Data Warehousing Department at Mobilink (MMBL)

• Trained an XGBoost churn-prediction model and a propensity model on customer data to power a manager-facing decision support tool.
• Designed logic so that customers with churn score >50% trigger behavior-based retention recommendations, while those <50% trigger propensity-based product/project pitch suggestions.
• Built a Streamlit web app demo for the CBO with drill-down navigation: region → regional churn → RM → branch → individual customer.

Database Intern at Pakistan Bureau of Statistics

• Supported a crime statistics modelling project: organized and prepared raw data for analysis.
• Performed data cleaning and structuring, and helped interpret statistical patterns within the crime dataset.

BS in Business Data Analytics (FinTech Major) – COMSATS University Islamabad (2027-06)