PROBLEM STATEMENT $-1$

Technical Problem Statement: Transforming Early Talent Engagement and Hiring

through Advanced Analytics and AI

Background: Unstop is an early talent engagement and hiring platform with a community of

approximately $8$ million students, freshers, and $0-5$ years working professionals. It enables

companies to brand, source, engage, assess, and hire talent. However, with the vast amount of

data available, there is a significant opportunity to leverage advanced data analytics and artificial

intelligence for enhanced talent engagement and hiring.

Challenge: The challenge is to develop a solution that can analyze the vast amount of data

available on Unstop and use it to enhance the talent engagement and hiring process. This could

involve analyzing job descriptions, company information, and candidate profiles to match

candidates with jobs that are not only relevant to their skills and experience but also aligned with

their career goals and preferences. The solution should also consider the dynamic nature of the

job market and the evolving needs of the companies and the candidates.

Objective: The goal is to invent a disruptive talent engagement and hiring experience powered

by advanced data analytics and AI$.$ The solution should be able to analyze large amounts of data

quickly and accurately, provide insightful recommendations to both job seekers and employers,

and ultimately enhance the efficiency and effectiveness of the talent engagement and hiring

process on Unstop. The solution should also be scalable and adaptable to the changing dynamics

of the job market.

Some Key Areas to Consider:

Data Analysis: The solution should be able to analyze large amounts of data and extract

meaningful insights. This could involve analyzing job descriptions, company information, and

candidate profiles.

AI and Machine Learning: The solution should leverage AI and machine learning to provide

personalized recommendations to job seekers and employers. This could involve using machine

learning algorithms to match candidates with jobs based on their skills, experience, and career

goals.

User Experience: The solution should provide a seamless user experience for both job seekers

and employers. This could involve designing intuitive user interfaces and providing real$-$time

feedback to users.

Scalability and Adaptability: The solution should be scalable and adaptable to the changing

dynamics of the job market. This could involve designing the solution in a way that it can easily

be scaled up or down based on the demand and can adapt to the changing needs of the job

market.

please write the stepwise code, because I don't know AI and ML