The main problem we are trying to solve here is to enable users to apply for jobs faster, by understanding the user behavior, we want to recommend the closest job titles to their CV, and based on the selections made in the past, we can learn a pattern of behavior. for example, the type of companies (size, industry), location, language, salary range, job title,etc.

We would like you to create a recommendation engine that has pattern recognition based on a combination of keywords, using different algorithms to get the closest match. This will use a supervised learning

• Given a user, return a list of recommended job descriptions
• The recommendations should consider the past combinations of selections, research, and clicks
• The recommendations should consider job descriptions that are viewed by other job seekers that are similar or resemble the given user
• The recommendations should consider how the user has rated past job descriptions, based on our 5-star rating system

Final deliverables include:

• All source code.
• A written report explaining the process and outcomes.
• test results of given data sets and simulations.

Students will connect directly with the employer for mentorship and supervision throughout the project, they may work with other interns or staff members.