BQML Team

**Acquired by OpenAI**• Enabled cache warmup in control plane

• Developing a non-relational database comprising of hazard-agnostic data to support damage prediction models

• Joined Google Big Query ML Team, which allows users to run ML models with SQL queries

• Sought statistical discount opportunities with CEFs and REITs

• Joined Google's Spanner Placement Team, which focuses on resource distribution within Google's SQL database Cloud Spanner

• Participated in a selective, intensive coding program intended for replicating the role of a full-stack software engineer• Developed an interactive and dynamic website that allows users to rate college dining halls, by performing frequent data exchanges through Google’s Firebase platform

• Maintained the content and data for Globaleur’s Destination Content API by locating activities, restaurants, parks, and other public venues for major cities• Supported back-end web scraping code with Python and Java

• Analyzed the statistical relationship between mosquito prevalence and environmental variables through Python regression models by implementing GLOBE Observer Mosquito Habitat Mapper and AppEEARS Land Cover datasets• Collected 157 data points to verify correlations between surface temperatures, biomes, and other environmental variables with the purpose of onsetting mosquito borne illnesses in humans• Showcased at 2020 NASA STEM Enhancement in Earth Science Seminar and author of Globe.gov blog