Non-Traditional Ways To Hire Data Scientists ﻿
The internet provides unprecedented and unlimited leverage to those who are skilful, creative and a bit patient. Here are a few non-traditional ways in which aspirants can exploit the incredible advantage that is the internet. Hackathons/Competitions AIM and ZS collaborate for a hackathon Kaggle has become the go-to platform for those who are looking to prove their mettle in machine learning. Like Kaggle, there are many popular hackathons, where both the aspirants and the recruiters can test their luck. MachineHack is one such platform, which consistently pushes challenging competitions. Winners apart from testing their skills, also stand a chance to win tickets to flagship AIM conferences and a potential job interview as well. Conferences Julia creator Viral Shah at MLDS 2020 Conferences are a great platform for networking. From rookies to senior professionals, everyone stands a chance to meet a diverse crowd from different departments and different companies. Pick a top conference in big cities, check their sponsors and companies which are participating in the form of presentations/talks. If you find your dream company, just make yourself available. In this way, you have a higher rate of landing a job than the dreaded delays of waiting for responses on emails you sent a few months ago. In India, Analytics India Magazine hosts 4 of the largest conferences for data science and machine learning enthusiasts. Meetups AIM and NVIDIA’s meetup Unlike conferences, meetups can be very niche, but that is advantageous to those who know what they really want. Top companies such as NVIDIA organise meetups, where the attendees not only get a chance to learn about cutting-edge tools but also gain attention from the hosting company. Because companies like those who can be immediately trained on their new products. Maintain Blogs and Repositories Blogging about machine learning hands-on guides or tutorials on popular platforms like medium, Linkedin or AIM Expert Network is slowly becoming the standard for newcomers as well as those who are looking for a career transition. Recruiters are on a lookout for people who are proactive. Your blogs with Github repository embed is as good as any resume can be. Candidate’s profile becomes self-explanatory, some consistency and authenticity to the content can land you top jobs. Do Podcasts and Vlog Youtube has become a treasure trove of data science resources. It allows people to record podcasts, webinars and conduct live code sessions, revolutionising pedagogical practices. This is like giving a skype interview at your own will in your own comfort zone but to multiple recruiters in one go! Use AI Train a model in such a way that can recommend jobs from across the internet based on your job profile. Yes, you have heard this before, and this can be your mini-Linkedin platform. Now land an interview using your model and flaunt how your own work got you where you are. A recommendation engine that you built to get an interview at a place that builds recommendation engines. Is there a better pitch than this? The good thing about all the above strategies is, if done right, you will somehow end up learning the rubrics of the subject you are pursuing, which you can leverage to land a job through the good old traditional routes as well. Data science has an overwhelming reception globally, it is hyped, but it requires a wholesome profile. From understanding problem statements to building pipelines to communicating it with clients, it comprises skills that can be portrayed through the ways mentioned above.
The internet provides unprecedented and unlimited leverage to those who are skilful, creative and a bit patient. Here are a few non-traditional ways in which aspirants can exploit the incredible advantage that is the internet. Hackathons/Competitions Kaggle has become the go-to platform for those who are looking to prove their mettle in machine learning. Like […]
The internet provides unprecedented leverage to those who are skilful, creative and patient. Here are a few non-traditional for Data Science aspirants.
["Machine Hack", "MLDS"]
["data science", "Go", "machine learning", "AI", "ML", "RAG", "MLDS", "Machine Hack", "Aim", "Ray", "analytics", "R"]
["AI", "machine learning", "ML", "data science", "analytics", "Aim", "Ray", "RAG", "R", "Go"]
I have a master's degree in Robotics and I write about machine learning advancements.