Inspiration
As students stressing out about the TOC this upcoming week, we decided to make a tool that makes it easier for students to explore different companies and decide which company booths they want to visit during TOC.
What it does
ticTOC is a web application that brings together information from Glassdoor and Handshake, including job listings and company information. Students can add companies that they wish to explore, and get a treasure load of valuable information to help them decide if they want to work there. Our main use case is for students trying to prepare for a job fair who are unsure how to prepare. Using our app, they could essentially use it as a study sheet to know what companies are looking for when hiring.
How we built it
We built a webpage from HTML/CSS/Javascript and collected career information from Glassdoor using the Glassdoor API. We then utilized Google Firebase as the underlying database to store an access the information we pulled from the various webAPIs. We used Javascript to interact with the data and pull relevant information to put on the webpage.
Challenges we ran into
We attempted to integrate Handshake by using the Handshake API. However, we could not obtain a Token key to access the information specific to Carnegie Mellon's Handshake. If we were able to access the Token key, we could get information about the TOC, specifically, which companies are attending. We could also view an extensive list of job postings on Handshake, and search those up on Glassdoor.
Accomplishments that we're proud of
Figuring out a neat way to easily incorporate Glassdoor into a CMU student's job search on Handshake. Making our app relevant and functionally useful to students like ourselves.
What we learned
Familiarized ourselves with various job search application APIs. Optimized and constructed a method for presenting the most relevant information for a student looking for an internship/job opportunity at a job fair.
What's next for ticTOC
We would like to access a token key for the Handshake API. We can then automate the process of deciding which companies a student should look up, and potentially using machine learning to present a student with the most relevant companies/job listings. We are also hoping to implement a more robust method of filtering and parsing the most relevant information, possibly using machine learning to make decisions about the information we pull from the web. This would also be useful for doing a "fit" calculation to see how well the student using the app would fit into the company they are interested in.
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