Data Science Jobs Outlook for 2018


Data Science Jobs Outlook for 2018

A combination of many fields, Data Science deals with the application of scientific methods, processes, and systems with the intention of deriving knowledge and understanding of data. The data used for processing into valuable information can be either structured or unstructured. With an increase in the number of entry level data science jobs, there has been a clear rise in the people applying for them. It is predicted that the number by the year 2018, one million data scientists will be required for handling big data related tasks. IBM has predicted that the demand for data scientists will soar to 28% by 2020 and the number of openings for data scientist will reach a whopping 2,720,000 by that year. The future looks bright for people who are trying to make it big in the Data Science domain. According to PayScale, the salary for Senior Data Scientist is $130,461 per annum, which is a paycheck worth striving for. Most people, who have an experience of 20 years and reach a senior position in the organization, shift to other profiles for a better paycheck.

Requirements for Data Science Jobs

You need a certain skill set in order to become a data scientist. Below are some skills that you should acquire for a glittering career:

1. Higher Level of Education is Preferred and mastery in a Data Science Tool

Almost 88% data scientists have at least a Master’s degree and 46% have PhDs. One should also be proficient in one of these two analytical tools:

  • Data Science R
  • SAS

Data Science R is the preferred tool for data scientists.


2. Good Grasp of Technical Skills

Knowledge of Python can be a great asset for anyone looking to make it big as a data scientist. Good grasp of Hadoop can add real value to your CV as it is preferred in many cases. Some experience with Pig or Hive can help you make a strong claim for the job. Coding or SQL Database may not be essential, however, some companies still swear by it. As you have to work with structured and unstructured data at the same time, some familiarity with unstructured data can be of great value.


3. Non-Technical Skills

A data scientist should have a logical mindset and good reasoning capabilities. If you do not have any intellectual curiosity, you won’t go very far in your career. This profile is suited to those who are on a mission to learn and take their everyday work as a challenge and derive pleasure after accomplishing their tasks. A solid understanding of the industry and how the business operates can be a wonderful asset. Your keenness to learn about industry standards and how to be profitable to your organization can help you climb the stairs of success with ease. Good communication skills are desired in almost every profession and data science is no different. You need to be able to communicate well with your teammates and managers. As you go higher in your career, you would get to interact with sales team who would have little to knowledge about technical mumbo jumbo. In order to convince them about your project, you would have to communicate with them in a manner that they can understand.

Career Path for a Data Scientist

You can start your career in the field of data science after completing your master’s degree in computers. You can begin your career as a Data Analyst or Data Scientist and work your way up the ladder and become Senior Data Analyst. With more experience in the domain, you can apply for the post of Data Science Manager. After a few years as a manager, you can even become Head of Data Science.

Competition in the Market for Jobs


Due to the immense possibilities in the field of data science, a lot of aspirants are lining up for the limited number of jobs. This has led to an increase in competition, which has made it essential for the candidates to learn the basics in detail. With a course at QuickStart, you can prepare well for the screening process of entry level data science jobs.

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