Aman Riat Email & Phone Number

Ottawa, Ontario, Canada

Toronto, Ontario, Canada

• Developed a full stack application to retrieve and display model configurations
• Utilized DynamoDB to retrieve and store JSON data
• Combined API Gateway and Lambda to accept requests and return desired information
• Implemented a React App with Typescript to take in user information and display data

• Developed a chatops application to manage AMIs through a slackbot and kubernetes
• Created github actions to automatically build and push docker images
• Contributed to development of a golang gRPC service to manage amazon AMIs
• Implemented a tekton pipeline in kubernetes that automatically versions and manage dependencies for release engineering builds
• Maintained prometheus and grafana helm chart to monitor internal servers
• Examined and compared bare metal kubernetes solutions to run for internal development

• Contributed to development of a dashboard to evaluate the quality of data to be used in time series forecasting
• Developed a full stack web app with React and Flask that satisfied customer requirements to process files and produce JSON
• Participated in week long hackathon to investigate using sentiment analysis in time-series forecasting
• Deployed and tested Kuberenetes deployments to be used in production
• Trained models to evaluate forecastability of data using a variety of metrics such as mean absolute error, entropy, etc

Ottawa, Ontario, Canada

• Trained, tuned, and evaluated machine learning models with sklearn to use in time series forecasting
• Used techniques like grid search, cross validation, mean absolute error, etc to train models
• Developed a dashboard to provide interpretability about models with pandas and dash-plotly
• Created an informative notebook with Jupyter to present results of a trained model
• Scraped web with python and used APIs to gather social media data to use in model training
• Created docker images and deployed images to kubernetes cluster

• Implemented a pipeline on kubernetes to train a machine learning model
• Refined docker containers to deploy to kubernetes
• Used software such as QGIS and SNAP to view and edit satellite imagery
• Coded unit tests to ensure production ready software
• Worked with geopandas to manipulate and process shapefiles
• Setup a database on kubernetes to hold geographic data