• Developed automated machine learning system to win data science competitions• Maintained and supported booth display frontend for major conferences remotely• Developed and deployed the backend for a web app for NIPS 2017 to show bias in AI andalso collect data from interactions by users and which is available to the public today

• Integrated various ad and usage networks onto the platform using C#/.NET• Created news scraper with Python to extract app mentions from different news sources• Added analytics support for ad spending and integrated a few networks for the feature

• Developed and maintained chat, data visualization, task, journal, and note management system for patient and therapist views using the Django framework which create more effective and efficient mental healthcare therapy sessions• Researched, prototyped, and implemented user stories in an Agile team• Semi-finalist in the Zahn Innovation Competition and part of the 2016 summer acceleratorcohort and utilized D3.js for interactive data visualizations using AlchemyAPI's sentiment analysis and sentence ranking features, created dashboard interfaces, and integrated platform into AWS and Azure

• Developed backend for an attestation feature for capital using a proprietary stack • Utilized Python, relational and object-orientated databases, in an Agile environmentalongside four other developers

• Designed and programmed a Python front-end to PyFLOTRAN which is a reactive flow and transport modeling software for subsurface processes.• Used PySide to leverage the power of the Qt framework, e.g., cross-platform, many GUI components, in Python. • Reduced coding skill burden on scientists by allowing them interact with a GUI