- Built a convolutional neural network to identify oscillatory patterns in sensor signals- Used Amazon Web Services’ EC2 instances to run docker applications with multiple instances working to distribute data to multiple AWS services including SQS, DynamoDB, and Timestream- Created and maintained DynamoDB, Timestream, and S3 databases to optimize data storage- Supported senior executives in designing AWS systems to boost product efficiency and reduce costs- Designed and implemented logic to calculate sensor event start times yielding a significant performance improvement along with drastic speed and cost improvements

- Ensured successful launch and redesign of new company website- Migrated Microsoft Access databases to Pervasive SQL database (Zen)- Built internal applications to facilitate user interaction with backend services

- Proctored exam environments- Provided insight and troubleshooting in software development

- Executed Machine Learning experiments in order to improve existing models- Provided feature engineering and analysis

- Built financial models - Researched potential clients

- Built several internal tools to provide data analysis- Provided machine learning models to analyze sensor lifetimes- Utilized sine wave regressions in order to measure the cycle rate of sensors to improve production machine learning models