Poseidon
Demo developed for the Citi Venture's Economic Mobility challenge at MIT-FinTech 2018 hackathon, which took place April 20-22 at the MIT Media Lab. My team was awarded the second prize.
See demo of output for cyber+security here
We find the competitiveness of hiring for each city by combining number of relevant jobs listed with number of resumes and an affortability factor.
Requirements
- python 3.5+
- pip3 install -e requirements.txt
Order to run notebooks
jupyter notebook-- to start jupyter notebook- run job_scraping.ipynb -- to scrape indeed.com for jobs
- run resume_scraping.ipynb -- to scrape indeed.com/resumes for resumes
- run affortability_scraping.ipynb -- to scrape numbeo.com for affortability statistics
- run poseidon_scores_calculator.ipynb -- to get Poseidon scores for cities and metropolitan areas.
Acknowledgement:
Scoping, ideation, and analysis was done in collaboration with Cyril Blank and Danny Fooba.
All code was written by Keld Lundgaard.