3 Skills to Boost Your Salary by 30%

Data Scientists in India earn an average of Rs. 10.8 lakhs per annum (LPA) (as per The Analytics and Big Data Salary Report, 2016). This is higher than the average salaries in IT, marketing, operations and even finance. Data Scientists in India are indeed a well-paid lot.

Even the most hesitant job seeker among you can rest assured that if you decide to make a career shift into analytics from another field, you’re very likely to see a jump in your earnings. What do you do, however, if you are already a data scientist? What additional skills should a data scientist pick up in order to increase her chances of commanding a higher salary?

Here, I will discuss 3 highly sought-after skills in the field of analytics. I would advise each and every data scientist to acquire these skills as it will raise their desirability quotient, and make them a valuable resource for any employer, present and prospective. In fact, I can give it to you in writing—which is precisely what I’m doing!

Learn more to earn more

Data scientists who know multiple tools are able to earn more than their less versatile peers.

The Analytics and Big data Salary Report, 2016 reveals that analysts who know a combination of SAS, R, Python and SPSS are able to command salaries that are 20% to 30% higher than the industry average.

This is a recent trend, one that has emerged in the last 3 years. Most analytics companies these days would rather use a variety of analytics tools than rely on just one to meet all their needs. This is why data scientists who know multiple tools are becoming more valuable.

The surest way for data scientists to render themselves invaluable is to learn multiple tools. If you know SAS, learn R and Python. If you know R, learn SAS and Python.

Trust me, the time and money you invest will be well worth it.

Add a dash of big data to your resume

Big data tools and technologies allow data scientists to successfully grapple with a) large volumes of data and b) unstructured data, both of which have come to characterize the business sector. Companies are generating huge amounts of data – far more than conventional tools can handle. Many of them are keen to analyze unstructured data, the kind that’s generated by social media platforms and machine sensors. Voluminous and unstructured data (i.e., ‘big data’) necessitate knowledge of big data tools.

Data scientists who familiarizes themselves with technologies like Hadoop, Hive, Pig and databases like Mongo DB, Cassandra DB will see their market worth shoot up.

According to the Analytics and Big data salary report, 2016 data scientists proficient in both analytics and big data earn 26% more than scientists who are only conversant with analytics. Given these numbers, adding a dash of big data to their resumes should be a no-brainer for data specialists.

Get familiar with machine learning

Machine learning is a set of analytical techniques that evolved from the study of pattern recognition in artificial intelligence. It includes techniques like clustering, neural networks, support vector machines and many others. Machine learning is very popular for a variety of problems including those involving optimization. As more and more businesses have begun to use analytics to optimize their complex processes, demand for machine learning experts has also seen gradual growth.

Right now there aren’t enough people in the industry who know machine learning, making it one of the top skills that every data scientist should invest in.


The top 3 skills that are sure to stand data scientists in good stead are:

  • Knowledge of multiple tools – SAS, R and Python being the most popular
  • Learning big data technologies and getting comfortable with NoSQL databases
  • Building expertise in machine learning

This is the best time to be a data scientist! Head on to our online analytics courses page to learn skills that will give a big boost to your salary.

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