• Created robust data pipelines in Python using Airflow (DAGs), automating data flows between systems, optimizing data processing, and enhancing system scalability by 40%.

• Leveraged Splunk SDK and query language to generate real-time graphs, providing stakeholders with visual insights into data irregularities of Priority 1 error.

• Developed Python scripts to monitor and detect data irregularities in pricing schedules, leading to a 60% decrease in issue resolution time, ensuring data accuracy and integrity

• Expedited data filtration and refinement of student housing database with over 16000+ data points

• Implemented data solutions by designing robust optimized and linkage scripts in Google Apps Script (Lightweight Javascript) that seamlessly integrated Google Forms with Google Sheets, reducing redundant manual work by 70%

• Developed SQL Queries/Formulas to form connections between Google Sheets and enable concurrent filling of data

• Co-engineered an Image Recognition System to detect license plates from 500+ drone/UAV-based captured images

• Customized and configured cutting-edge deep learning models, including YOLOv5 and WPOD-net, to achieve object detection accuracy of 88% for license plate identification

• Streamlined Python BeautifulSoup4 web scraping scripts using Selenium, cutting down manual work time by 60% to scrape data of over 4,000+ Indian-origin MNCs

• Modeled a Database in MySQL to store data schematically, redesigned Python scripts to extract, transform, and load (ETL) data for analysis and trends visualization