Data scientist is someone who knows how to extract meaning from and interpret data, which requires both tools and methods from statistics and machine learning.

Data Scientist is the one who analyses and interpret complex digital data. While there are several ways to get into a data scientist’s role, the most seamless one is by acquiring enough experience and learning the various data scientist skills. These skills include advanced statistical analysis, a complete understanding of machine learning, data conditioning etc. Programming Complexity is high.

You need to have the knowledge of programming languages like Python, Perl, C/C++, SQL, and Java—with Python being the most common coding language required in data science roles. Programming languages help you clean, massage, and organize an unstructured set of data.

Switching careers to a data science role, a good strategy is to start incorporating data science skills into your current role so it will be much easier when you make the transition. If you haven’t already, start by adding data-driven decision making into your current role.

A Data Scientist, according to Harvard Business Review, “is a high-ranking professional with the training and curiosity to make discoveries in the world of Big Data”. Therefore, it comes as no surprise that Data Scientists are coveted professionals in the Big Data Analytics and IT industry.

According to the forecasts of the World Economic Forum, by 2024 data analysts will be in high demand in companies around the world. … This is further confirmed by IBM, which claims that the annual demand for data scientists, data developers and data engineers will lead to 700,000 new recruitments by 2024.