My findings from interviewing over 2500 data science aspirants

. 5 min read

The Good, The Bad, and the Ugly.

Being a business acquisition associate at GreyAtom is no mean feat. With the phone ringing off the hook, I am riveted to my ergonomic armchair for a huge chunk of my day. The upside of my role is that I get to speak to people of all stripes and hear out their stories. This is an aspect of sales that some people fail to appreciate. This is also an element that brings a human touch to a role that is often considered rote.

The Plot

At GreyAtom, we have a rigorous screening process in place that includes a telephonic interview, which sometimes also doubles up as a career counseling session, followed by an in-person interview. So, I thought I would take this opportunity to speak about my amazing takeaways from interviewing over 2500 data science aspirants – young and middle-aged, dropouts and C-level execs, non-techies and data nerds, from India and abroad.

We get the most inquiries from mid-career professionals, i.e. folks with around 5 to 8 years of work experience. The very first question, right off the bat, is whether they are capable of pulling off an extended learning program. The undertone of self-doubt as to whether they can ‘learn’ past their early to mid twenties varies from subtle to in-your-face.

A Happy Outlier

It is amusing to hear them gasp when they are informed of aspirants extending across the age spectrum and the success they have achieved on the hiring landscape as well as in the corporate hierarchy. I am still reminiscent of a mid-career professional, afflicted by corporate burnout and self-doubt, and aggrieved by a job that paid well, but had gathered inertia. What started out as a business acquisition call turned into career counseling, with a tinge of motivational pep talk. Six months later, the same gentleman is now placed as a senior associate in the data science division of one of the biggest MNCs. On a follow-up call with him, he exuded self-confidence and pride in his career transition. More importantly, there seemed to be a sense of momentum in his new job.

The above case is an outlier. A majority of aspirants who call in are primarily interested in moving up the pay scale or simply getting a better job. GreyAtom’s primary value set has been knowledge over frills and quality over quantity. Part of our career counseling effort is to inform aspirants of these values and the fact that GreyAtom doesn’t assure job placements. However, GreyAtom’s career assistance services help students build the necessary soft skills that improve their chances of landing their dream job.

Cultural Drag

In India, students and young professionals are used to being led by the hand in most matters, particularly, education and employment. I see the downside of this grooming during my conversations over the phone – from being utterly clueless about their career goals to being hunched over from carrying the weight of parental expectations and unsolicited recommendations. Sometimes, I feel like I am on the other end of a youth helpline.

At GreyAtom, we emphasize on self-learning and self-reliance. We encourage our students to research the market for data science and the growth forecasts from industry experts. Throughout our flagship Immersive Learning Data Science program, we have our students build soft skills like communication, blogging, and presentation. It’s these elements that build self confidence and a strong sense of purpose, which go a long way in making successful professionals and leaders.

Building soft skills and a strong sense of determination is especially important for those who lack prior experience in data science or whose undergraduate coursework didn’t involve any hard sciences. Surprisingly, we get a lot of calls from non-STEM folks who want to dive into data science.

So far our efforts to get people to self-start themselves have yielded great results. Most of our students have gone on to chart the difficult terrain of hiring landscape all by themselves and landed jobs with startups and, MNCs, extending from mid-level to top tier. Some have also gone on to build de novo data science teams within their existing workplace and a few have built successful startups.

From Retail Banking To Data Science

One of the most striking cases was that of a well-spoken lady with a background in retail banking, who wanted to transition into data science applications in banking and finance. I still remember her perfect articulation of her apprehension and self-doubt as I persuaded her to research data science and its applications. After a week of intense research, she enrolled in one of our ongoing cohorts and is performing exceedingly well, finishing up in the 90th percentile in her cohort. This is a great example of how a non-STEM background is not an obstacle or contraindication for a career in data science.

The Pre-requisites

To get your foot in the door, you need to build a solid footing in math, statistics, and computer programming. While this might seem daunting, with a little effort, it is actually an achievable feat.

I usually ask aspirants of all backgrounds to enroll in free introductory courses in math, statistics and computer programming language, preferably Python. There are a plethora of quality courses available on Coursera, Udemy, and other MOOCs platforms. Once they build their foundational blocks, with some more effort, they can ease themselves into our flagship program. Building foundational knowledge is also a great exercise, in that it is a teaser into what they can expect when they enroll in a data science program. We try our best to make sure that applicants don’t squander time and money enrolling into a program that they end up having a hard time keeping up with.

Smug And Gloat

Pardon my blustering, but this is the part where I get to puff up my company. Fortunately, I will attempt to temper the boastfulness, by citing experiences of some of our ex-students. Following are some of the excerpts of student testimonials as to why they love GreyAtom’s learning environment and offering.

  1. We don’t emphasize on accreditations or affiliations because data science is not about big branding. It’s about real knowledge, producing outcomes, and designing a scalable product. This is captured in a nutshell in our motto “Learn = do real work” and we would like to stick to our values.
  2. Although we are for-profit, we don’t chase after money. Our profits are the result of leaving our students with worthwhile skills and capabilities that help them upgrade their careers and find dream jobs.
  3. Our training occurs on a state-of-the-art, agile, in-house, scalable platform – Commit.LiveTM, using industry-sourced data sets. This makes the learning outcomes relevant to folks in the hiring departments of big corporations.
  4. We love feedback and take it fervently. While we didn’t begin as perfect, we believe we are inching closer to it with every amend and update we apply to our educational offering.

Why I Would Never Change Roles

While most other disciplines and sub-disciplines in India have incredible visibility and a structured database of information, data science seems to be fraught with lack of information or, at worst, misinformation.

The other handicap that data science in India suffers from is of the cultural sort. Ageism and a lack of self-starter spirit seem to mar the ambitions and derail the plans of several professionals trapped in a limbo of dissatisfying jobs.

While GreyAtom is putting its back into clearing the air around data science through its community partner, we are still taking baby steps towards the destination. The second challenge is comparatively elementary to target and this is what motivates me to come into work everyday. A business acquisition role has its good and bad days, its own stresses, but assisting aspirants in turning their lives around is one of the most fulfilling element of the role. I wouldn’t settle for any other role.

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