City of San AntonioData Scientist / Public Safety Innovation Specialist
Jun. 2021 - May. 2022San Antonio, Texas, United StatesAs a Data Scientist with the City of San Antonio, I leveraged my analytical skills and programming knowledge to support the San Antonio Police Department's operations and strategic planning. Key contributions included: Murder Log Analysis: Utilizing Python, Pandas, and Applied Statistics, I facilitated in-depth statistical analysis of murder incidents during 2020 and 2021. I automated 30+ statistical tests to ascertain the relationships and significance of various demographic, historical, and location-based variables, augmenting our understanding of crime patterns. SAFFE Activity Database: Partnered with the Chief's Technology Team, I created a SQL database for the SAFFE Activity application. This tool enhanced our SAFFE officers' capacity to track and record their community outreach efforts efficiently. Crime Predictive Modelling: Using Time Series Analysis and Regression techniques, I devised models to predict Uniform Crime Reporting (UCR) totals for future years. These projections provided critical insights for proactive department planning and resource allocation. SWAT After-Action Form Scrapper: Employing Python and Beautiful Soup, I innovated a method for extracting data from Microsoft Word documents, thus improving data accuracy and turnaround times. This technique was used extensively for SWAT after-action form analyses. Bexar County Scrapper Project: Using Python, Pandas, and Selenium, I designed a web scraper for efficiently retrieving historical data on criminals from Bexar County court records using minimal personal identification. This tool was pivotal in gathering bond, bail, and probation data for ongoing murder investigations. Through these projects, I have demonstrated a unique blend of technical expertise and a deep understanding of public safety operations, contributing meaningfully to the department's data-driven decision-making process.