We have been in the field of Analytics training for over 4 years now (current and previous organization) and have trained personally over 1000 students in both SAS programming as well as advanced analytics including both retail and corporate clients.

One of the most repeated queries I field from my students is “How do I get in?” or “How do I convince an Analytics company to hire me ?” or “I have 10 years experience in so-and-so industry, how do I make a switch to Analytics?” . If only I had a rupee for everytime I was asked this question, I guess I could have retired by now! (or maybe 10 Rs/question).

Well, there is no singular answer or approach to enter the industry, off-campus freshers face a tortuous task in breaking in, to get hired you need to have experience in Analytics and to get experience in Analytics, you need to be already hired somewhere. Its an age old challenge.

Back in the day, all technical trades were controlled by guilds (for e.g. carpentry, masonry or blacksmiths) which acted both as facilitators to the chosen and entry barriers to the upstarts. To enter the field, a young man (or person) would have to grovel before an established artisan to get an unpaid apprenticeship in return for lodging and food. This was generally unpaid labor but in the bargain the apprentice gained experience and the artisan free labor. After a few years the apprentice would be granted membership of the guild and be free to setup on his own.

Jump to the 21st century and transplant this to Analytics, How do YOU break in ? The challenge a 1000 years after the establishment of guilds remains the same, to be hired you need experience under your belt and to be experienced you need to get hired.

A few clarifications for people trying to break in

• First off, there is no formal qualification or degree required to be an Analytics professional. (You dont need fancy Maths/Stats/Engg degrees, I have seen arts graduates become Subject Matter Experts in collections analytics).
• Secondly, there is no age limit, 40 year olds have made the jump and done extremely well.
• Its a job seekers market, provided you have reached the magic figure of 12 months experience.

Experience in analytics is King today, people who have experience can literally dictate hiring terms.

But how to get that initial experience? Therein lies the heartbreak, though there is a way, just like it was thousands of years ago, apprenticeships (we call them internships now), you have to convince a company, any analytics company to hire you either at a very low salary or even no salary in the beginning. Face it, you need them more than they need you at this stage. Anything to get that valuable CV line about experience in. This is typically a call which freshers just out of college are able to take easily. But for those coming with previous industry experience will find difficult to make the jump. Whether to make this jump or not is a decision you have to take.

I have seen 30 year olds leave stable jobs to start in Analytics at Rs 12,000 /month salaries. A year later they are already at their previous levels. 32 year housewife who took up a SAS programming course was offered a 10,000/month contract for 3 months at a small analytics company, she is now a middle level manager in the analytics arm of a major MNC. The pattern is evident, do whatever it takes to get working once you have acquired a few skills; whether through some training courses or self study.

Analytics companies do not care about your educational qualification, formal background, if you have prior analytics experience, you are a rare commodity and you will be snapped up.

That said, what are the skills that one needs to even get a foot in the door. I have one word for that – “SAS”. SAS programming jobs are probably one of the easiest ways to get a foothold in the industry today. SAS certifications (exam costs some USD 200, quite cheap for the benefits it provides) on your CV can act as a substitute for SAS programming experience. The companies will treat you as a known commodity if you have cleared the certification exams and will increase your chances of shortlisting.(I will insert a disclaimer here – since our organization specializes in SAS training for certification, this opinion piece may be considered biased to convince the reader to enroll for SAS training, that is not the objective, I am merely stating an observation)

Secondly, there are SAS jobs and then there are SAS Analytics jobs. One mistake that people can make is to take an initially higher paying pure SAS programming job over a SAS Analytics profile. Candidates need to be very aware of the nature of work they are getting into, a company which offers work in predictive modeling or data mining using SAS should always be preferred over a pure SAS programming job. A mistake here could mean a career of reporting and ad hoc requests versus definitely more glamorous side of Predictive modeling. Beg, borrow, steal, kill or even pay, but get experience of predictive modeling under your belt. A small difference in the beginning but over 30 year career can mean totally divergent paths.

A note here: Typically startups are more likely to hire people based on attitude/aptitude rather than a CV. They provide the best opportunities for people who really want to break in.

In sum :

• Study a lot, it takes time to master any new technical skill, typically to reach an employable skill level in SAS and basic analytics will require upto 500 hours of training, practice and self study. (Target 4 hours a day over a period of 3-4 months)
• Be prepared to spend time in the trenches, you have to be mentally ready to take a salary cut, maybe a huge one to get that elusive experience initially. (Target internships and startups here, have a target of 8-12 months experience under your belt before you start looking around after this)
• Make intelligent choices , in your career, even a 1 week project in predictive modeling using say regression could make all the difference.(Beware of pure SAS programming jobs, they may only be on the reporting side, keep trying to gain experience in data modeling projects)
• Every big MNC has an analytics arm, if you are already working in such a company, pull all strings to get into an allied project which you can leverage for experience, or an internal transfer. (I know a guy who was in the BPO arm of a major MNC, he bugged his reporting chain for 1.5 years before they finally relented, today he is travelling all over the world as an SCM analytics consultant!)
• Those who play it like they have nothing to lose are the ones who win big, bring your attitude with you