Are you struggling to clear data science interviews? Not sure how to showcase your lack of data science experience? We have put together a comprehensive course just for you. Come and learn about the different aspects of data science interviews, and get access to tons of videos, hundreds of questions, and plenty of resources in the ‘Ace Data Science Interviews‘ course!
Now, let me present the two sides of a debate going on in my mind:
One of the most common reasons quoted for rejection of Freshers (or people with non-analytics experience) for analytics jobs is lack of experience! What an irony for someone young wanting to enter the field! They can’t get experience without a job. They can’t get a job without experience!
A quick survey of about 20 freshers (trying to enter the world of analytics) I did before writing this article, revealed that on an average, they had been rejected 25+ times due to lack of work experience – even for junior roles.
It is dis-heartening to see the difficulty faced by these people!
Having said that, I have been on the other side of the table for more than last 4 years. Let’s look at what one of my colleagues has to say:
We were expanding our in-house analytics team from 2 members to 5 members. Instead of hiring an experienced professional, we thought of bringing really smart people (straight out of college) on-board. Post their joining, we took them through a very structured induction and training programme and even got them certified from the SAS training institute (all of this, at the cost of delaying important projects for business owners). We were hoping to get loyal and smart analysts, who would pay for these investments through high quality work.
3 months after joining, the first person left to start his own venture. 6 more months later, the remaining 2 people left the Organization to join other companies offering them better salaries!
Imagine the kind of costs, the team leader had to bear. Loss of business from key stakeholders, loss of time, knowledge and efforts. To make it worse, they were back to where they started – a 2 member team! I think, he was lucky that he did not get fired!
P.S. While I am saying Freshers, what I refer to is people with no analytics experience.
How do we solve for this problem? Lets look at the reasons why employers prefer people with work experience over Freshers:
- Attitude towards work and Maturity in taking decisions – Most of the employers feel that people out of college take immature decisions and need to be mentored on attitude towards work. This is less of a concern with people shifting careers, until and unless there is a specific reason from the past.
- Time to bring a new person up to speed – An analyst typically takes anywhere between 2 – 6 months to come to speed with the subject. It can easily be a year before you see anything significant coming out of an analyst.
- Short life span – Because of the demand for trained professionals in the industry, Freshers tend to leave jobs either in search of higher pay or expectation of better role / work. Leaving for better work / role as such should not be a problem, as long as it is actually the case.
A few things which can work as strengths for freshers:
- Ability to learn – People fresh into their roles, typically have higher ability to learn. It might be because of higher willingness or because they have been just out of an environment conducive to learning.
- No need to un-learn old habits – This is a big advantage with freshers. You can mould them the way you want. You want them to put a framework before touching data – train them in that manner. Try doing it with someone who is in the practice of doing it the other way.
- Ability to look at everything with a fresh perspective – How good can an analyst be, if he does not ask questions? Experienced people find it difficult to do so, as they may already have a perspective on the subject.
So, here is the strategy, which a fresher needs to follow:
Address the concerns of the employers (listed above) and emphasize on your strengths.
Well, everyone needs to carve out his or her own way. But here are a few tips, which might get you started:
- Start learning analytics early – there is no substitute for hard work and real knowledge. Even if you spend 3 – 4 hours every week reading about the subject, or undergoing trainings at MOOCs (e.g. Coursera, eDX), doing certifications in the last 2 years of your college, you would know more than a lot of people in the industry (at least the theoretical part of the journey).
- Become an expert on at least one programming language – You can choose the language you want. I would choose Python or R, if I was passing out in near future.
- Participate in contests – Now that you have the knowledge, apply it! You can participate in coding contests, hackathons or analytics competitions on platforms like Kaggle. It gives you immense learning while you compete alongside the best data scientists in the world.
- Contribute to these communities – Whether it is your contributions on Github / stackoverflow or Kaggle, all of them will count immensely when scoring a point with the recruiter.
- Attend events and network with people in the industry – See if your college is arranging some talks / conferences on the subject. Are there seniors / batchmates you have, who are already in the industry? Reach out to them.
- Get an internship – Internships are a good way to gain work-experience. We have 2 summer interns in our office this summer and none of them had analytics work experience before. By the way, they are doing a fabulous job (to all those recruiters who think work experience is mandatory)
- Try getting a job in companies which are open to hiring freshers / non-experienced people. For example, companies like Mu-Sigma, Fractal, WNS, Citi etc. are open to hire people without prior work experience.
If you work on even some of these pointers, you can address the concerns mentioned in the article before. Next, emphasize on your strengths and make a mature decision – no short term decision please!
Are you a recruiter / a fresher / or experienced analytics professional? What is your take on this debate? Who do you prefer to recruit? Why? Any tips to freshers wanting to join the industry? Please share them through comments below.