One Step

Candidate Landing Page
Candidate Result Page
Recruiter Landing Page
Recruiter Landing Page - More Women in Tech

Inspiration

Job Seeking has always been a very exhausting task. We wanted to make it simpler thus introducing "One Step" to the world! It doesn't stop there. We have a special place for WOMEN in TECH!

What it does

Job Seeker uploads a resume. Our intelligent application analyses their resume and suggests job role and the companies for which they will make a good fit!

Recruiters enter search criteria such as the role they are looking to hire, Number of candidates to be shortlisted and whether they have a preference for WOMEN in TECH. Based on the parameters, previously hired records and N number of machine learning algorithms, we retrieve the top candidates who will be the best fit for the role.

How we built it

Web Application using Python, HTML and Django framework. Machine learning techniques such as decision trees, random forest, neural networks, naive Bayes classifier, Gaussian Bayes classifier and support vector machine were implemented in Python.

Challenges we ran into

We didn't have real-world training data and testing data. Handling extraction of features from few resumes required a lot of processing.

Accomplishments that we're proud of

We achieved a combined overall accuracy of 87% during testing of resumes.

What we learned

Hacking is always fun! Team Work >>>>>> Individual Work

What's next for One Step

Advancing the algorithms to take the location of the candidate and the job posting into consideration. Incorporate Optical Character Recognition in the heavily formatted resumes.