Leveler

Inspiration

We wanted to develop a tool that helps remove bias in the hiring process, evaluating candidates solely on their qualifications. Personal information on a resume has been known to introduce gender bias, and we aim to prevent this by providing employers with anonymized resumes that highlight a person's skills without revealing their identity. Our goal is to create a fairer job market where talent is recognized and valued, regardless of demographic factors. By focusing on qualifications alone, we hope to empower diverse candidates and promote a more inclusive workplace.

What it does

After signing in, users enter their qualifications and experiences. This data is anonymized to remove information that can reveal a candidates gender, ethnicity, religion and socio-economic background. Their qualifications are matched to the job description and a match score is generated. The anonymized information is forwarded to the employer

How we built it

Frontend: We developed the client-side of our web application using streamlit, crafting interactive user interfaces and components.

Backend: We used PropelAuth for user management and authentication. We used spacy for anonymization and SBERT for resume to job description matching.

Anonymization: Spacy

Matching: SBERT

Challenges we ran into

It was our first time using streamlit so it was a challenge to learn a new technology.

What's next for Leveler

We plan to add Zero Knowledge Proof to verify a candidates qualifications on an employers behalf.

Built With

• propelauth
• python
• sbert
• spacy
• streamlit