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Career in a Rut? Analytics could be your Answer

Published on 19 February 18
Career in a Rut? Analytics could be your Answer - Image 1
Data is the new currency and the data whisperer is the new king. The question is no longer if you should upskill with analytics and data science, but what kind of analytics skills you should add to your repertoire.
There is great demand for people who are adept at handling data and can analyze that data for effective decision making. But what does it take to make it to the top in this field? What are the skills needed? Weighing in on this, Snehamoy Mukherjee, Senior Director for large Data Science, Big Data, Machine Learning and Analytics engagements at Axtria, says We need people with the desire to learn and work hard, which I believe is the most important skill. Everything else, is trainable. On the hard skills front, ability to understand business, apply analytics frameworks to the business problems, think through multiple insights that can be provided to the client, what problems we can solve for them using the data and which algorithms and statistics to apply to which business problem are the skills that students should develop.
The Analytics Market Today
Be it building a recommendation engine to a chat bot to a market mix model, it’s all about data – and this needs data savvy professionals who can extract insights out of seemingly random data. The Analytics market in across the globe continues to grow steadily and organically, and that is sound growth. We don’t have a bubble in this industry, where thousands of wannabe analytics shops opened overnight, with crazy funding from private equity or venture capital firms. There is demand for folks with sound analytics skills. There is of course a huge demand in the US market, which gets fulfilled offshore. says Snehamoy.
There is a wide demand and supply gap between what the industry wants and what the candidates are offering. It is not enough to just know to work with data, but it is essential to also unearth what that data is saying and present it in an understandable manner based on which the management of an organization can take strategic decisions that will drive the company.
Expressing his opinion on the current analytics talent pool, Snehamoy adds, The quality of Analytics professionals in the talent pool is deteriorating by the day. The reason for this is that with the increase in the volume of analytics workforce, the quality of training that organizations were able to provide in-house earlier as compared to now, which has also deteriorated.
With the hype and buzz around analytics, a lot of available training in the analytics space has not been focusing on the actual industry needs – and instead been focusing on tool based training, which is not an effective learning methodology. Analytics is all about understanding the underlying concepts and processes, and not just learning to work with one or two tools.
Snehamoy is of the same view. Instead of structured trainings, organizations are now relying on self-help modules to train the staff, which leaves people to their own means and motivations to learn. This is not ideal. Analytics needs to be taught in a very rigorous manner by people with experience in the field and there are no text books to learn analytics unlike programming or finance, he says.
What Needs to Change
What we need is people to learn analytics and data science as applied in the industry, with focus on practical learning. You can master analytics online with the various courses that are offered here, but you should also attend some boot camps to acquire get industry exposure and learn the skills and build a network.

Pick up a project on Kaggle or Hackerearth and start learning R, Python or any other tool. You'll start learning things gradually. Start from small eventually you'll end up big. All the best. Make a portfolio of projects that you do with the code, visualizations, analysis in words, conclusions, thoughts and everything around that project.

Here are Some of the courses that can help you master the concepts required for getting into Data Analytics
Now to ensure that your resume grabs eyeballs when you apply to an analytics firm needs some preparation. The preparation would be different for a fresher than for someone who already has some work experience under his belt albeit in a different domain. For a fresher generally engineering or maths/ stats graduates the focus is more on analytical problem solving and exposure to some programming language and then they can apply to analytics firms for jobs.
There is no one size fits all solution. Your situation could be different (educational background, experience etc.), this is where experts and mentors from Data Science field understand your profile better and guide you in the right path.

Like what Suzy Welch says "Your mentor doesn't need to have seniority over you." A mentor just has to do something better than you do.

Here are some of the experts who are willing to help you achieve your career goals. They conduct a personal one–to–one over Skype and discuss your profile and areas for improvement.

  • Ganapathy Govindan (Specialist: IT career transition into Analytics)
  • Sabrish Surender (Specialist: IT career in Analytics)
  • Anmol Sunsoa (Specialist: Shaping future in Data Analytics)
  • Ujjyaini Mitra (Specialist: Data Science, Career movement to Data science)
  • Mario Lewis (Specialist: Data Science, Big Data and Analytics)
  • Jose Munoz Mata (Specialist: Data Science, AI, Career Development)
  • Harpreet Dua (Specialist: Data Science, Business Analytics)
  • Arihant Jain (Specialist: Data Science, Predictive Modelling

  • If you are coming from a different field, then you can explore mentors, who could help you in your career progression.

    I hope that you find my article useful and you’ll have a good start in your search for Analytics job in 2018. You can post your comments below to discuss on the points that I have highlighted in this article.
    Good luck!

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