Should You Consider A Career As A Data Scientist?

Available Jobs

Data Scientists are currently in high demand with thousands of job openings per year.

Starting Salary

As a qualified Data Scientist, you can expect a starting salary in the range of 30K to 50K.

Expected Average Salary

As an industry average, you can get a hike of 15% for next few years.

Analytics & Data Science

Data science is the domain or industry focused on working with all aspects of data - from data collection to analysis and reporting. Data analytics is the name of the skill (and art form) of working with data to draw insights. Business analytics is the practice of applying the concepts of data science in a business setting.

Analytics involves framing research questions, defining and conducting experiments, collecting data, analysing the data with tools and business domain know-how, interpreting the results and communicating the results to stakeholders - along with recommendations for future action.

Why Data Science Is Important

Data is at the heart of everything we do. Technology and science have disrupted traditional businesses with such force and velocity that it’s impossible for a business to thrive without data today. Technological advancements have increased the number of devices and systems that can generate data. To make sense of the data, we need trained and skilled analytics professionals who can derive insights from the data to understand its implications.

Professionals with diverse analytics skills are in high demand. If you can work with data and communicate with stakeholders, you are at the top of the recruitment interest list.

What To Learn

Data Science is an umbrella term for various methods and techniques. There are many different skill sets that one needs to acquire. However, these skills vary greatly depending on the environment and portion of the workflow you are focusing on.

To begin with, one can pick up one or more of the powerful and most used analytics technical tools such as:

• Microsoft Excel

• R programming language

• Python programming language

• SAS

• SQL

• Big Data tools (Hadoop, Spark, Storm, MongoDB, Cassandra etc.)

How To Get Started

• Build proficiency in the use of an analytics tool.

• Learn statistical and numerical analysis techniques to be able to analyse any kind of data.

• Analytics and Data Science is not purely about number and statistics. Once you have learned the basics of data analysis and are confident about your skills, you need to learn how to apply those skills in a business context.

• To gain a foothold in the industry, you need to demonstrate that you have a practical understanding. A demonstration of the skills you have gained, goes a long way in convincing recruiters. You can gain practice in several ways: internships, contests, competitions, community projects, personal projects and of course, learning on the job. In fact, in many places, the easiest way to gain some experience is to apply data analytics to your current role and demonstrate value - adding to your resume and skill sets a very valuable trait.

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