There is no doubt that data is the new oil of the 21st century. We are swimming in a vast ocean of data and every company is looking to hire talent to make sense out of that data. With so many openings for data professionals, hiring the right candidate has become a very difficult exercise. The demand for core skills sets such as AI programmers, data scientists and data engineers is going through the roof raising the overall salary expectations. This has obviously attracted a lot of professionals to move towards a data career. But here lies the problem, how do you ensure that the candidate you are picking is the right candidate? How do you go through the dozens of resumes to figure out the right set of people to move forward with the formal interview process?
This demand supply gap has also attracted a lot of fake profiles. The need to weed out the average candidates and focus on the right candidates has never been stronger. Current processes involve manually going through the resumes, which may not tell the whole truth. Screening interviews are very time consuming and sometimes done by people who are not qualified to make those distinctions. Result, too many hours wasted in the screening process and the risk that you may be leaving out good candidates and focus on the wrong candidates.
What hiring managers need is an objective process which could put all the candidates on the same footing and subject them to the same testing criterion. A process which is designed to not only test the true worth of the candidate but also rank order them based on their skills and aptitude. This is where Datascholar's unique platform shines. Our platform is designed to find the best candidates and weed out the rest. Imagine feeding a list of candidates to this tool and within a few days you have a complete objective picture in front of you. You can use the ranked list to screen candidates and even use the score as a criterion for your final hiring decision.