Every time I attend any analytics forum or interact with students, two questions stand out on account of number of times they are asked:
I am an undergraduate (or any other) student & want to pursue career in Analytics, what should I do?
or
I want to build a career / shift my career in Business Analytics, how should I go about doing so?
Further, I receive multiple queries through mail / social media / comments asking the same. In order to make sure these queries are addressed in best possible manner, I thought it’s best to write an article on this and provide a starting platform for everyone.
While the subject itself is wide, I’ll provide an overview of various things which can be done and focus on specific sub-topics through additional posts later on.
Before I delve into the ways of building an Analytics career, let me quickly cover why to build a career in Analytics first.
Why build a career in Business Analytics?
Analytics, as an industry is set for exponential growth. With more and more data being available in digital form, need for smarter, faster, data based decisions is only going to increase. Consider following facts to substantiate what I am saying:
- According to Harvard Business Review (October 2012 edition), job of a data scientist is the sexiest job of 21st century.
- According to the McKinsey Global Institute (In a May 2011 report): “By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.”
Imagine what would be the number across the globe…
I understand Analytics will become big, but I don’t know how do I start a career in Business Analytics?
Its difficult for a newbie to find out the best way to start a career in Analytics due to following reasons:
- The industry in nascent stage, hence, it is difficult to find proper guidance.
- “Analytics” or “Business Analytics” are losely used terms, which makes it difficult for people to understand and appreciate the role
- There are limited structured & well laid out path which you can follow to enter the field.
While the first factor will improve with time and I had written an article mentioning second point here, this post aims to address the third point.
Two approaches to build a career
Like any other employment skill, there are 2 approaches to enter / start an analytics career:
- Approach 1 – Get hired by a company which trains you (on job / internal trainings) on the necessary skills. These would be companies which have Analytics in their DNA and use it for their day to day decisions. While this approach is better from long term perspective, it takes time and investment (especially if there is no structured training in the companies). Some of the companies known for using cutting edge Analytics (in India) are:
- Technology leaders: Google, Facebook, Linkedin
- Banking, Financial Services and Insurance (BFSI): Capital One, American Express, ICICI, HDFC
- Telecom companies: Idea, Vodafone, Airtel
- Analytics Consultancies: Fractal, Mu-Sigma, Absolutdata, ZS Associates
We have also prepared an comprehensive course on how to ace data science interviews. If you are expecting to face an interview with any of these companies, that’s your jackpot!
One of the alternate route to get into these companies can be internships. So if you have a 2 – 6 month break, give a try to becoming an intern in these companies.
- Approach 2 – Get Business Analytics related certification: While these certifications provides you with the technical skills required, these would not be able to compensate for experience on the job. Following are some options of training available (in India):
- For people with work experience, various leading academic institutes run certification courses. If you have the required experience and resources, I would recommend the course from ISB
- For freshers, there are certification courses run by various institutes, including Analytics Vidhya. Getting these certification courses can increase your chances of getting hired in some of the best companies.
What else can be done?
While these are specific paths for starting a career in Analytics, there are smaller steps you can take to increase your awareness. Some of them are mentioned below:
- Continue reading on the subject: Keep reading about the subject through various blogs and communities.
- Attend Industry forums: There are various industry forums, meet and conferences which you can attend to gain understanding of the subject. DataHack Summit (held annually) is one of the places to meet some of the best people in industry
- Try internships: Internships are awesome way to start your career. They provide you a flavor of the work before you take a plunge and the employer gets to assess you without significant investments.
- Connect to people: Since it is a small industry today, most of the people know each other. Find out how can you connect and talk to people in industry. They are your best sources of information.
- Go through training material available on the web: Google provides basic training for Google Analytics free. There are various websites running basic courses which can be accessed freely. Some universities provide access to course notes freely. Consume as much as you can.
- Books: Read some good books on the subject like Scoring Points (on Tesco); The new Science of retailing, The Signal and The Noise are some good books on the matter.
If there are any other resources which you have found useful to learn more on the subject, please add them in comments below.
Image credit: aibworld.net
If you like what you just read & want to continue your analytics learning, subscribe to our emails or like our facebook page
You may also like: Common myths about a career in Business Analytics: Busted!
Kunal is a post graduate from IIT Bombay in Aerospace Engineering. He has spent more than 10 years in field of Data Science. His work experience ranges from mature markets like UK to a developing market like India. During this period he has lead teams of various sizes and has worked on various tools like SAS, SPSS, Qlikview, R, Python and Matlab.
