RequalifyMe

An interactive tool that allows you to find the best career path for you based on your skills.

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Inspiration

The 2022/2023 recession has affected many individuals around the world. Among many negative outcomes, widespread layoffs and hiring freezes have likely been the most impactful. Experts imply the jobless rate may increase roughly 30% by the end of 2022. What’s more, the projections for 2023 suggest an even more substantial surge. Companies are cutting costs on both technologists and manual workers, where Amazon’s direct warehouse workforce declined by approximately 100,000 in 2022, making it the most significant drop in the company’s history. The technology staff tends to find new positions within days, which may not be the case for less qualified workers. For that reason, we have created RequalifyMe - a portal facilitating the transition to high-demand jobs.

What it does

  • The main page provides users with a search bar, where individuals can put their current skills from a set of prepared ones. The skills together with the most common ones are obtained from our database via backend API.
  • Afterwards, the user is redirected to a page listing all job categories, where they can see the most relevant jobs, as well as the match between their skills and the required ones for the position. This again required us to extend the backend API to calculate the job-to-individual skill match.
  • After picking the industry the user can see jobs specific to the category. There, information like industry-leading firms, position-specific skills required and employability rating over the past and predicted future is depicted. The data is obtained from the database and is presented in a clear-for-the-user way.
  • The outlined user journey is depicted on our screenshots attached to the project description.

How we built it

There were three main components of our project. Marcelina focused on gathering, analyzing and parsing data, in a format that could be put into our database. That included finding jobs together with past and future employability indices, tagging necessary skills and grouping jobs into categories. Antek developed the backend API in Python django and set up the mysql database. Emilia and Matteo worked on all pages of our frontend. This required creating the search bar with keywords suggestion, listing the most relevant jobs to the skills entered, as well as user-friendly and vivid data visualization.

Challenges we ran into

  • Finding relevant and high-quality data for the project required a lot of Marcelina’s time and frustration.
  • A substantial amount of bugs on the frontend-backend communication.
  • Coming up with a relevant and original idea took a lot of our time, and we were left with less time on executing the plan.
  • Suboptimal time-management left us with little time on debugging and improvements.

Accomplishments that we're proud of

  • An interactive and user-friendly frontend offering a great user-experience.
  • Creating a scalable backend storing relevant data in a database enabling us to easily add new data points in the future.
  • Efficient use of our team members’ preferences and strengths with a strong outline between frontend, backend and product development.
  • Finding and successfully executing a project in a high social value area.

What we learned

  • The project improved our understanding of backend - frontend communication.
  • The frontend team discovered a lot of useful frontend libraries such as GraphQL.
  • Investigating the needs of users requires a lot of creativity and is time-consuming.
  • Large backend services in Python can lead to technical debt.
  • Finding relevant and high-quality data can be a hard and tedious problem, and small teams may be unable to achieve that in a short period of time.
  • We can learn a lot about frameworks and programming from other hackers.

What's next for RequalifyMe

  • Adding more data points related to jobs and tagging them with the appropriate skills.
  • Extending the UI with information like relevant courses online and gender employability ratio.
  • Going in the direction of automating data harvesting and processing.
  • Deploying the app on an actual server.
  • Promoting the app among individuals most vulnerable to job cuts.
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