6 months. 4 years. 20 years. Could you guess what these timelines mean for anyone who is working in the data science industry in 2021? Any guesses?
OK, let’s break the riddle.
6 months – that’s the average hiring period for any company to close the position of data scientist in India.
4 years – the average time frame for a junior data scientist to scale ahead of and get promoted to the next senior level in a data science project.
20 years – Average time frame for an IT engineer to become a highly trained, expert level data scientist with a salary that is in the top 5 percentage population.
So, you can imagine the kind of efforts and struggles professionals have to take in their journey on how to become a data scientist in India.
It’s that kind of year that started with a brave volume of optimism at the back of the first COVID-19 wave and then slipped into the second wave, delta wave, and slowly people started losing hope if things would ever go back to normal. Sadly, things aren’t going back to normal, but here’re few good things that would bring a smile to your face, especially if you are pursuing a data science course or plan to do so in the near future. The data science market grew 500% this year compared to what it was in 2019. In fact, in the coming months, the market is going to go bullish on data scientist hiring trends and you would see 10x times the hiring volumes demanded from top tier company like software development company, marketing and sales, e-commerce, sports analytics, media and entertainment, and companies involved in healthcare. If we were to do classification research on the top 10 technology jobs that you should eye this year amidst fears of coronavirus pandemic, the top 5 titles would go to data scientist and its sibling profiles from Big data engineering, analytics, and AI development.
Despite knowing there is a process and lineage involved in reaching the final destination of becoming a top tier data scientist, a majority of professionals grow highly impatient with their career development.
If you are looking for serious tips on how to become a top data scientist in India, I would suggest you track down the available projects for the Junior data engineers and AI developers in India. These offer ample opportunities to those looking to build a career in data science and could often fast track your growth in terms of experience gained through some serious hard coiled projects from top tier customers.
What’s it is like to be a Junior Data Scientist in India?
Firstly, for most titles on LinkedIn or any other professional networking site, a majority of data scientists refrain from using “Junior” or “Senior” in their titles. Fair enough, because these titles are mere nominal and often misrepresent the kind of data science projects they could be handled in a practical environment.
Secondly, the titles are arbitrarily fixed by the hiring industry just to distinguish between professionals with different levels of skills and experiences in the same industry, irrespective of what projects they might have worked on.
Therefore, we always say that the best certification from top tier AI ML and Data Science course could do so much good to your journey in how to become a data scientist in India. Never estimate this.
A majority of these roles involve working with various kinds of Python and R programming platforms for TensorFlow, Keras, Sci-Kit Lean, Pandas, Numpy, and PySpark. These streamline a clear mandate on the projects for Regression/ Linear Analysis, understanding of Deep Learning for Generalized Linear Model, K-mean and naïve Bayes, and so on. What comes really handy for Junior data scientists is their ability to surf through challenging deadlines that come in working with tight deadlines, lean teams, and extremely customer-centric empirical research.
Nonetheless, the junior data scientist title is something to cherish and if you are just starting off in the industry, it could be the best thing to happen to you.
Big tip: If you focus on solving an unsolved problem, you could become the top data scientist in the world, not just India. Think about it.