Grace Dai Email & Phone Number

Seattle, Wa, Us

Seattle, Washington, United States

While working at Amazon, I had worked as a host at a nearby restaurant and during my time off, my former manager asked me and five others to help start up a new upscale cocktail bar in Pike Place. I learned how to bartend for this position and have been bartending and running the social media. Increased follower count from 200 to over 2000 (and counting) in the span of 10 months. Captured and curated DSLR imagery for the feed and had images used in Seattle publications such as Eater and The Stranger. Was interviewed for Seattle Met Magazine as a bartender.

Greater Seattle Area

Rearchitected, designed, and engineered an 8x decrease in loading times for our internal tooling utilizing AWS Lambda, Aurora, React and Typescript to create a faster and sleeker user experience.Implemented a multi-stream pipeline that processed billions of records by utilizing Amazon Kinesis Streams and Flink, eliminating a one day delay on aggregated data.Built a service to periodically export over 50 million records of daily aggregated data to a data visualization tool for use by other teams, resulting in a 30% reduction in trivial intake requests.Reduced customer service contact calls related to internet connectivity issues by 4% by constructing an on-device diagnostic tool to analyze connectivity data and suggest resolution steps for customers.Extraneous Contributions:Mentored a 2022 summer intern to receive a full time offerWon the Alexa Excellence Q2 2022 Hackathon

Greater Seattle Area

Implemented Python program to retrieve real time device data from Kinesis Analytics and send to CloudWatch data storeEmbedded dynamic CloudWatch graphs onto interface that were customizable with user inputLearned to use Kinesis Streams, Kinesis Analytics, CloudWatch, Bootstrap, React, HTML/CSS and enhanced Python skillsDelivered internal website for efficient access to real time device data

Cleveland/Akron, Ohio Area

Developed a working prototype for more user friendly experiences at GoodyearProgrammed a recommendation algorithm using cosine similaritiesWorked primarily in Java and Python, dabbling with Bokeh for an interactive user interface

Processed data through Opendx to create visual representations of tensile strength in polymersGraphed data in GNUplot Coded macros in Microsoft Powerpoint to create animations more efficiently that showed the correlation between the images and the data Worked primarily through a Linux terminal with Mobaxterm