Inspiration

Most of the talent available is not actively looking for a job making it hard for recruiters to attract candidates in to their recruiting funnel. Meanwhile, passive candidates ignore most of the out reach done by recruiters.

"Behind one of those cryptic recruiter templates, is a dream job sitting in your inbox."

What it does

Currently: PassivelySeeking parses recruiter outreach, augments it using a knowledge graph and request more information.

Our goal is to build integrated bots to require zero touches from the passive candidates until all the required information is gathered.

How we built it

For better or worst, we built this using python, flask and a sql database.

Challenges we ran into

Scrapping gently on a time crunch is hard.
Gathering labeled data to train a proper ML model
It turned out to be "fancy" fuzzy match and playing probabilities.

Accomplishments that we're proud of

Extracted information from recruiter emails and mapped it to external data source to provide salary ranges, location, and more.

What we learned

18 hours is not enough.
You might still need unit tests during a hackathon! Testing saved us.

What's next for PassivelySeeking

This can be seen as a 2-sided marketplace (candidates and recruiters).

Integrating with email clients and LinkedIn InMail to automate response and information gathering on behalf of the passive candidates
Build a conversational AI
Assist candidates with scheduling, interview preparation and salary negotiation
Incorporate human in the loop to give a premium experience
Start building a relationship with the candidates

Once a critical mass is obtained on the candidate side, we can start helping recruiter by:

Help them target candidates that are more likely response to their messages
Assist recruiters in composing relevant and effective messages personalized to the candidates