The term “Data Science” can be traced back to 1974, when Peter Naur suggested it as a replacement for “computer science.” Data science was a topic for the first time in the International Federation of Classification Societies conference conducted in 1996.The job of a data scientist involves collecting huge amounts of data, analyzing them, isolating the relevant information, and then using programs such as SAS, R or any other to produce ideas which can be instrumental in enhancing the productivity and efficiency of the business.The responsibilities of a Data scientist include pulling data from various sources, employing machine learning tools to organise data, processing, clean and authenticate data, finding information and patterns in the data, building predictive models, presenting data effectively, and suggesting solutions. 

However, as discussed above, data science is simply a broad term for many different types of job posts and duties. These individuals are commonly referred as Data Analyst, Business Analyst, Software Developer, or Marketing Data Scientists just to mention a few.

Some of the most important technical data scientist skills are: 

• Statistical analysis and computing. • Machine Learning. • Deep Learning. • Processing large data sets. • Data Visualization. • Data Wrangling. • Mathematics. • Programming. 

A data scientist can be defined as a business intelligence (analytics) professional dedicated towards gathering, dissecting and explaining data so as to inform decisions within an organisation. 

The data scientist job borrows components from multiple conventional and technological occupations like mathematician, scientist, statistician and a computer programmer. 

The procedure entails advanced analytics methodologies, including machine learning and predictive models, while observing scientific laws.

• At times, data scientists are forced to carry out hypothesis development and testing among other tasks using bulky raw data in a bid to identify customers’ and markets’ traits among others as well as detecting patterns in the context of finance, cyber security, stocks trading among many instances.
• Businesses would often employ data scientists to mine information for them to predict how their customers would behave; discover new revenues, detect a possible scam or meet other such business needs. 
• In addition, they analyse data for healthcare providers, academic institutes, governmental bodies, sports clubs, among other organisations.
• However, interest for data scientist has steadily increased, with data science skills being in high demand from companies seeking to extract valuable information from the growing pool of “big data” in order to exploit AI and ML solutions so as to build new classes of analytic tools.