Author: Utkarshini Edutech

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DATA SCIENTIST as a Career

An upcoming Revolution!? Call me a fabricator, but in 2014 the UN declared, “Data Revolution” to highlight the impulsive and silent change which will unknowingly change the course of time.

The world is awash with data. We generate as much as 2.5 quintillion bytes of data every day. Data Revolution perceives each byte of data as a stepping stone and considers it informative in some way or the other. The trailblazers of the Data Revolution are the data scientists. The propaganda of how to make use of it is a hefty task which a data scientist adopts. Basically a data scientist has to make sense out of unstructured data and yield useful results out of them.

This particular career has been declared as the best job in the US, 3 years in a row and from the looks of it is here to stay. With an average pay of about 6 lakhs INR and a ceiling value all the way upto 20 lakhs INR, this job profile has a lot of scope, satisfaction and affluence. Google, Facebook, TCS, Cognizant, HP, Wipro and many other tech giants are in pursuit of data scientist to clean and model data according to their needs.

  This is a brief overview of the skills which an aspirant is expected to have:

  • Comprehension of machine learning techniques and algorithms like k-NN, Naive Bayes, SVM, Decision Forests, etc.
  • Jack of data science toolkits, such as R, Weka, NumPy, Mat Lab with excellence in at least one of them makes you highly preferable
  • Competent interpersonal and communication skills
  • Versed in data visualisation tools like D3.js, GGplot, etc.
  • Proficiency in using query languages such as SQL, Hive, Pig or  NoSQL databases, such as MongoDB, Cassandra, HBase (this varies from company to company)
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.
  • Good scripting and Optimised Coding approach (this is pretty much implied)

A weird policy followed when hiring for this job is that the companies hardly judge you on your academic stats, provided you are well acquainted with data science concepts. Having a data oriented approach and projects affiliated to big data analytics and machine learning are an add on. FAQs in interviews include Real Life Scenario Data sets which will be provided to you and your approach is going to testify your skills. Good aptitude always helps.

To groom your skills on data science refer sites like kaggle.com. Brush up your basics from sites like edx.org and coursera.org.  Refer sites and apps like Internshala, letsIntern and Frapp for internships and sites like Monster.com, Nakri.com and Glassdoor to learn about job opportunities in data science.      

Hallelujah Data!

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