ZocialGPA was a company that created a social media behavioral analytics platform for employers to screen potential employees for dubious content and behavior on their social media profiles. The application computed a social “GPA”, using natural language processing (NLP) algorithms to analyze a user’s social media profiles. The platform was hosted and auto-scaled on Amazon Web Services (AWS), and the backend was written in JavaScript and Python.
I joined the ZocialGPA team as a Software Engineering Intern, but eventually became the lead of the team, managing a total of 4 Software Engineers. My primary responsibility was to design and implement a highly scalable and efficient software ETL stack, which was used to build datasets from various social networking platforms, including Facebook, Twitter, and LinkedIn.
In addition to this, I developed NLP and sentiment analysis algorithms to derive “social GPA” scores from a user’s social profiles. This required a deep understanding of both the underlying data and the specific requirements of the platform. I also refactored and modularized the entire company codebase, to enable efficient component-based auto scaling with Apache Stratos and AWS.
Another key contribution that I made to the project was the implementation of a mobile-first web end user interface for the platform, as well as a redesign of the internal company management console. Overall, my work on the ZocialGPA platform was a challenging and rewarding experience that allowed me to apply my technical skills and problem-solving abilities to a real-world problem.