MOUZAM FATIMA

As a professional with a bachelor's in pharmacy and a master's in data science, I offer a unique blend of skills poised at the intersection of healthcare and technology. With expertise in pharmaceutical principles and data analysis, I am well-equipped to drive innovative solutions, optimizing patient outcomes through a harmonious integration of pharmacy and data science.

Studied Computer-Aided Drug Design. Acquired in-depth knowledge in utilizing computational tools and techniques to design and optimize drug molecules. Applied principles of bioinformatics, molecular modeling, and structure-based drug design to contribute to advancements in pharmaceutical research.

Poster on CRIME DATA ANALYSIS FOR THE CITY OF LOS ANGELES

Led a critical data analysis project for the City of Los Angeles, focusing on crime data from 2020 to present. Leveraged an open data platform, I analyzed over 6,600 reported crime entries, extracting insights into patterns and trends. Utilizing features such as date, time, victim demographics, and geographic coordinates, the project visualized crime rates over time and identified prevalent crime types across neighborhoods. The analysis included hotspot identification for specific crimes based on geographic information. This project not only enhanced public safety strategies but also showcased my expertise in data visualization and crime pattern analysis.

Analysis of Manchester City Football Club's Decadal Match Data

This project endeavors to extract and analyze a decade's worth of match data for Manchester City Football Club (Man City) from FBref.com. The primary objective is to harness this data to craft insightful visualizations and construct an interactive Power BI dashboard. The methodology incorporates web scraping using Python's BeautifulSoup, data refinement with Pandas, and visualization development through Matplotlib and Seaborn.

Graph-Based Optimization Methods for Production Scheduling

Led groundbreaking project on "Graph-Based Production Scheduling Optimization." Applied advanced algorithms, meta-heuristics, and graph representations to minimize make span, reduce delays, and avoid resource bottlenecks. Expertise in critical path analysis, job insertion heuristics, graph coloring, and network flow optimization. Demonstrated success in both static and dynamic scheduling models through case studies.

• Tech Mahindra via Valliappa Foundation, Certified in Medical coding course
• Power BI for Data Analysis