Developed and tested unreleased AR/VR products, ensuring high performance and user experience. Developed 20+ data models based on SQL queries to upgrade the management repository. Executed Exploratory Data Analysis (EDA) on 10+ sources of 50+ columns and performed data cleansing to generate refined and operational datasets. Creating a PLX dashboard for reporting and Visualization Monitored the flow of incidents and assigned their priority levels. Formulated and managed reports showcasing the day's progress in Excel. Collaborated with cross-functional teams (engineers, designers, PMs) to refine AR/VR features Worked with Waymo to collect, validate, and process geospatial data for Google Maps integration. Assisted in improving map accuracy by labeling and verifying real-world navigation data. Managed large-scale data labeling projects using Google Sheets/Excel for machine learning training. Created and maintained scheduling systems to streamline data collection and processing workflows. Ensured high-quality labeled datasets for AI/ML model training. Environment: PLX dashboard, Python, GoogleSQL, Scikit-learn, Bug, Looker, BigQuery

Developed ETL pipelines and Python to process and transform large datasets from multiple sources. Managed inventory data for high-demand radio products, supporting large-scale events such as games, concerts, and conferences with daily orders exceeding 200 radios. Developed SQL-driven reports to monitor inventory levels, order fulfillment rates, and demand fluctuations, ensuring seamless distribution for major events. Created Tableau dashboards to visualize key performance indicators (KPIs) for operational reporting. Utilized SQL for data cleansing, data transformation, and data quality checks. Collaborated with data scientists to deploy machine learning models into production Automated data ingestion and visualization processes using Python Environment: Python, SQL, Tableau, Scikit-learn, Splunk