When we were trying to find a job online, we found many websites didn't cover all the information we care about. When we look for jobs, we are not only concerned with the work itself, but also with the cost of living, population density and safety of the city in which we are going to work. So we are going to create a platform that can help us achieve this function, which will help us find the ideal job and city to live！
What it does
Provides candidates with an enhanced talent acquisition experience. Better job, better live!
How we built it
Build backend algorithms in Python with open data from other online sources and integrate all algorithms with Google Cloud Platform Design a user friendly web server for dreamjob.ai
Challenges we ran into
How to use the open data, such as climate information, housing pricing and crime data, to empower our recommendation algorithms and Google Cloud Platform to increase quality of job searching
Backend algorithm! Scientific way to figure out which job and which city is the best choice for the candidates. And it increases quality hire, decrease time to find a ideal job and continue to improve matching over time
What we learned
How to use Google Cloud Platform
What's next for dreamjob.ai
We can optimize our dreamjob.ai website and add more new features to better help candidates find their dream jobs.
Built With Python 3.7, Bash, Zillow API, Google Cloud Platform, HTML, PHP, Flask, Bootstrap
Contributer Zhengqiao Zhao, Chen Chen, Lin Li, Siling Chen
Our dreamjob.ai efficiently and scientifically provides candidates with an enhanced talent acquisition experience.