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Are you an IT professional ready for a change? Or perhaps a recent graduate interested in a career in data science and business analytics? Talented data scientists are needed in a variety of industries and there are openings for any level of expertise.

What kind of a person is best suited to become a professional data scientist? Left-brained, for sure. This is math, computers and logic. But, as I hope to demonstrate, you will need a bit of wizardry in you. Prophecy, divination, and foretelling come with the job. So, go get your wand and let’s talk.

Here’s what you will have to deliver, Mr. Potter (or is it Hermione?).

Predictive analysis: Facts and data are useless unless you can use them to predict and intervene. You must identify, assess the effectiveness of, and evaluate trends so the client can integrate predictors and interventions back into the workflow, improving performance.

Optimization of product placement and inventory: Any company that delivers products efficiently needs to streamline logistics flow and storage to be competitive. Think Amazon.

Analysis of user data for online services: Social networks, news sites, and search engine optimization for internet ad placement require gathering and modeling user data for effective marketing.

Application of your wizardry to such diverse questions as art preferences, bank loans, social services and air traffic control is to ordinary muggles nothing short of magic. But it is magic without which the modern world can no longer function.

What skills must you master? What do they teach at Hogwarts School of Data Sciences?

One essential tool is R language. What is it? Here’s what Wikipedia says:

“R is an open source programming language and software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.”

Being open source, knowledge of R can be easily obtained, but an online or university course might be better suited for most. As with everything in life, practical skill trumps passive understanding. Find something that teaches you R programming and how statements are executed in R. You should understand data structure and how to import and export data in R. You will also need to know how to apply DPLYP functions. You should master the spectrum of association rules and Apriori algorithm. Clustering methods such as K-means, DBSCAN, and hierarchical clustering are employed frequently. And, of course, to present your product, you will need to be able to use graphics in R.

Do you need datascience certification? That would depend upon where you intend to start. In any case, you must document some mastery of the techniques I’ve listed above. Having a certificate rarely hurts, and it can go a long way in getting you credibility.

The best case to be made for doing a certification course is that you can get your feet wet with realistic data science projects. To convince a prospective employer that you can do the job, you need to be able to talk about projects you’ve actually done. If you are just switching to business analytics from another IT field, the next best thing to real-world experience is almost real-world projects.

So, how to find a data science position? Networking to find your first job is the most effective method, as long as you network with the right people. This means people you can help, not just people who can help you. Get to know people in the industry and find out as much as you can about their needs and challenges. Then look for ways you can solve their problems for them.

Once you get an interview, the crucial task is to convince them that you can do the job. Being able to talk specifics about the projects you’ve done is the most important thing. They will also want to know whether you are the right fit for their team (that’s why the personal interview is so important). Will they like working with you? But equally important is for you to feel good about working with them. For this reason, be yourself. The time to dazzle people with wizardry comes later, so don’t try to impress with smoke and mirrors.

And don’t cast any spells, yet.

I’m the founder of Shoppykart.in an e-commerce company.I am passionate about online customer acquisition, Data analytics, and project management and relish the opportunity to discuss, write and share my thoughts on these subjects.