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Inspiration
Given the current job market in tech, all our teammates struggle a lot to find a software engineering role.
What it does
It extracts available market data, analyzes the data, and creates plots that can inform job seekers about the current market. For example, users are able to see how many job postings are made per day and where such postings are made. With this information, job seekers can meaningfully tailor their job-searching strategy.
How we built it
We utilized Python mainly for this project so we used Streamlit for data visualization, building the web application, and deploying the web app.
Challenges we ran into
- We could not build it by using Taipy. We found Taipy's documentation a bit unfamiliar
- We lacked more workforce for the project. Only two of us worked on this project
- Unfamiliarity with new tech was a challenge but we quickly adapted over time
- The timezone difference was a big challenge as we were not able to collaborate in real-time. ## Accomplishments that we're proud of We have successfully crawled the data based on multiple sources, cleaned them, and built data visualization just solely by using Python. We got ourselves exposed to Streamlit, Taipy, and other new frameworks by learning them through experiments. ## What we learned
- How to crawl a website using Octaparse
- How to clean data using Pandas
- How to build a data-driven website using Streamlit
- Deployment
- Collaboration ## What's next We initially imagined IntuiJob as a job portal with meaningful insights and market trends provided to our users and recommended jobs based on their preferences. In the future, IntuiJob will have these integrations along with a database connection such that users can sign up and log in to receive notifications about market analysis and potentially apply in strategic ways.