In the past few years, a plethora of data science job roles have originated, but it’s really difficult to differentiate among them distinctly. Besides, the skill set required is different for different data science job roles. For big data aspirants, fortunately, the job market had kept hot in the past several years, given the unprecedented rise in the generation of digital data. As a matter of fact, 90% of all the world’s data has been produced in the last two years alone. Herein, we will be discussing different job profiles that are popular at the moment in the data science domain, and the work associated with them.
The post will help reveal the job descriptions for many data science roles for which hiring is ‘on’ in the global job markets.
Top data science skills in U.S. 2019
This job position specifically has a lot of scope for Hadoop specialists. A big data architect is needed at an organization that would like to develop a big data environment within its premises, or maybe, in the cloud. Such professionals act as a link between big data scientists and the data science needs of the firm. They are responsible for handling the full life process linked with a Hadoop solution. The typical job duties comprise generating requirement analysis, data science app development and design, platform selection, drafting technical architecture, testing, and application of a proposed solution.
Data Visualisation Specialist
A data visualization specialist is an individual who is held responsible for editing and creating visual content that comprises graphs, charts, and maps. The job involves transforming data into presentable visuals. In this role, you offer technical, editorial, and visual instructions. You help make data tell a story about itself.
Big data professionals in this job position make sure that the huge data frameworks are interconnected and architected. Here are a few of their primary job responsibilities:
- Decide about the auxiliary requirements of databases through careful probing of programming, applications, and customer tasks.
- Generate database architecture through effective planning of the proposed framework.
- Instate database frameworks by producing flowcharts, and deploy suitable access methodologies.
- Handle database execution by settling application advancement challenges, identifying perfect qualities needed for parameters, incorporating and assessing new discharges, responding to client issues, and finishing support.
- Offer database assistance using coding utilities, and answer questions asked by clients.
A big data career as an AI developer requires you to find ways to incorporate deep learning, machine learning, and artificial intelligence concepts into business processes to make the business more profitable. The skills needed for the job comprises hands-on experience in coding & programming, and familiarity with specific coding languages such as Python, Java, C/C++, Prolog, and Lisp, among a few others. As a data science aspirant, try learning as many ML coding languages as possible, while keeping Python and R on the top…