Diversity+

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Inspiration

Research shows that underrepresented groups are often disadvantaged in the process of recruitment – even though in many democratic countries, discrimination on the grounds of ethnicity, race, religion, sexuality or gender is prohibited.

Over the last decade, the weak position of underrepresented groups at different levels in the labor market has become a subject of heated debate in the world. The debate generally revolves around factors that affect the macro level structure of employment of, for example, immigrants, their descendants, the LGBT community, etc. The disadvantaged position of underrepresented groups is explained as a consequence of either discrimination, or that immigrants lack relevant social capital, language skills, wrong job search strategies, relevant job skills, etc.

When discussing the underrepresentation of these groups at an organizational level, the recruitment process is often referred to as critically important, and a radical way to enhance diversity is specifically targeting prioritized groups that are sometimes underrepresented so that the organization gains value from a diverse workforce.

What it does

Diversity+ focuses on uniting diversity-driven employers with people of color, women, veterans, older workers, individuals with disabilities, and members of the LGBTQIA+ community. This application caters to all women and men of color and everyone impacted by employment discrimination based on age, military status, sexual orientation, abilities, gender, immigration, employment history, or religious preferences.
Individuals can create a profile, upload a resume, and then can easily apply to desired jobs. Employers can add postings on the website to seek their preferred candidates.

How I built it

Tech Stack: Backend: Django, Django Rest Framework (to create the APIs), Simple JWT (for backend Authentication), GDAL, GEOS, MapQuest GEOCODER Frontend: Next JS, Axios (to send requests to backend), MAPBOX Database: Postgres (Postgis) Storage: AWS S3 Bucket (to store all resumes) Deployment: Vercel (frontend), Heroku CLI (backend)

Challenges I ran into

Implementing the location feature in the Job Posting: I used MapQuest, GEOCODER in the backend to generate the coordinates of the address which any employer is adding in the model as text field, and passing those coordinates to MAPBOX in the frontend which will then help to render the map for each location. Working with GDAL and GEOS libraries was painful and caused a lot of issues at first.

Topic Statistics Feature using aggregate in the backend: Worked with aggregate function in the models.py file

During Deployment: Some filters weren’t working due to presence of ‘+’ sign that was affecting the URL field. I fixed the error and now it works all good.

Accomplishments that I’m proud of

Created this project single-handedly in such a short period of time. The application helps in giving opportunities to underrepresented groups.

What I learned

Working quickly and efficiently in a time-bounded setting Time management and organization Check simple solutions before assuming complex problems

What's next for Diversity+

Integration of AI to suggest to job seekers which job postings are the best according to their resume, and they should definitely apply to. Creation of more filters to improve job postings.