The gap which we find prevalent is, how one decides, what career to choose, which higher degrees to choose, what skills to learn, and which trainings to attend. The purpose of this project is primarily focused on all such questions and showcase a way to transform data into a graph.

About the Project

The world is constantly evolving cutting across boundaries, religions, caste and gender into one massive global community. Because of this globalization, entrepreneurs are born creating billions of jobs, every job creating the demand for numerous skillsets, and every skillset demanding a training need. The fortunate individuals who are exposed to such trainings in the very beginning of their career or childhood, lands into lucrative jobs and others, who don’t, keep the search going for many years before they decide to continue what they are doing or take an alternative, merely for a salary hike.

There are businesses offering such training free of cost (especially through the Massive Open Online Courses) or charging a fee for enrolment. And many other industry players, have created platforms keeping jobs as their primary focus or helping individuals to connect with people who can then provide a lead for landing in such jobs. Much has already been done to help companies hire the best talents and help such talents find the right job.

Data Requirements

We need to create a data collection system, which we can create internally, containing all the alumni and students of Department of Mathematics and Computational Sciences. This system should internally function as a student portal where they feed in their details from CVs/Resumes and it gives back a well formatted and standardized resume in return. A sample system would look like below:

Once this portal is adapted by students, we should augment the data collected from this portal with the data available about the alumni of the department. All this data should be persisted in the MongoDB.

Data Science Opportunity

Following would be the use-cases which could be possible from the data:

  • Given a profile, provide a career map consisting of Degrees-to-Pursue (DTP), Skills-to-Acquire (STA), Trainings-to-Attend (TTA), Jobs-to-Land (JTL). The order is important.
  • Helping academia to design such DTP and TTA. Since, these two will always be focused on JTL, learning will never be boring for anybody.
  • Helping companies in choosing the right DTP for finding the right STA and suitably create a more coherent job description keeping in mind the industry standards.
  • Helping to build Industry-Academia and Academia-Academia collaboration to strengthen the effort for creating a rich talent pool.

The data should be represented as a graph which connects every student member and alumni to their skills, jobs, schools, companies and knowledge.

Data Science Challenge

To create a graph database, we have many challenges from collecting data to implementation phase. Some of the challenges are listed below:

  • Designing the student portal and making it to be adapted by .
  • Finding out the alumni information from department records or scrapping from LinkedIn profiles.
  • Identifying all the possible subjects, predicates, objects to create the triples to be stored in a graph database.
  • Designing a portal for every individual student to provide them with insights.

Probyto is collaborating with academia, businesses and organizations to develop a prototype for Talent Connect. We welcome your feedbacks and happy to partner with you or your organization. Please contact us to get more details.

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