May 2023 - Aug 2023

Data Analyst Intern at State Farm Insurance

Utilized DBeaver for in-depth health data analysis, delivering critical insights pivotal for informed policy enhancements. Enhanced efficiency by optimizing SQL queries, ensuring swift data extraction and empowering timely decision-making. Innovatively integrated DBeaver with QuickSite, revolutionizing the SAS-to-Excel process for seamless monthly health reporting. Developed a dynamic Model Point file, elevating pricing function analysis with heightened speed and precision. Spearheaded an impactful Health Analytics Proof of Concept (POC), orchestrating an impressive 85% data migration success to AWS, showcasing the transformative potential of cloud-based analytics solutions. Automated SPAA report generation, unlocking a 25% efficiency boost and streamlining operational workflows.

June 2021 - December 2021

Data Scientist Intern at Microbase Computers

Enhanced data analytics & reporting capabilities by implementing scalable ingestion routines, combining real-time & batch processing with Advanced Data Modelling, leading to a 25% increase in data processing speed & accurate A/B testing outcomes Developed ETL/ELT processes with AWS and Big Data technologies, reducing processing costs by 20% and increasing analytical depth and variety by 50% Identified and resolved architecture inefficiencies by implementing machine learning-driven optimization strategies, boosting data processing efficiency by 30%, and improving team productivity by 25% through automation and enhanced data reliability

February 2021 - April 2021

Data Science and Business Analyst Intern at Sparks Foundation

Leveraged Python and scikit-learn to forecast student performance, leading to a significant rise in pass rates. Developed a precise Linear Regression model, attaining a remarkable 95.22% accuracy in predicting student scores for 9.25 study hours. Implemented OCR techniques to streamline data processing, efficiently converting text documents into digital data.

February 2024 - June 2024

Data Analyst at ABCEDARIAN

Engineered ETL pipelines to process large datasets with Python, SQL, and Apache Spark, ensuring data accuracy and efficient data flows for downstream analysis and reporting Developed and fine-tuned machine learning models, including regression, clustering, and predictive modeling, using scikit-learn and TensorFlow, delivering actionable insights that enhanced decision-making process Designed and implemented real-time data visualization dashboards in Tableau and Power BI, enabling data-driven decision-making and improving overall business efficiency

July 2024 - Present

Data Analyst at REBECCA EVERLENE TRUST

Redesigned and merged internal/external scholarship tables in Aspects DB, streamlining data access and improving data management efficiency by 20% Automated data flow between Jotform and Azure DB using Python scripts on Azure, reducing manual entry errors by 50% and improving data integration efficiency Resolved Azure SQL DB connectivity issues, minimizing downtime by 30% through firewall reconfigurations and implementing temporary MySQL solutions