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Data Scientists translate a massive amount of data collated by organizations to gain new insights, identify trends and find ways to streamline business practices. The growth of data is phenomenal, in 2020 alone, 50x more data will be generated than it did in 2011thus there is no surprise that the importance of Data scientists is gaining manifold over the years.
It is the responsibility of a Data Scientist to make sense of this raw unstructured big data to analyze it and draw intelligent insights for strategic business decision formulations.
What makes this job so unique is that data scientists require a very specific skill set which includes programming, coding, data management, statistics. Another indispensable skill set is Data Analytics, the art of converting intelligent insights from data sets. Data analysts collaborate with IT teams, management and/or data scientists to determine enterprise goals.
The demand for skilled data scientists has risen over the years as organizations walk on the digital transformation path. As big data movement becomes mainstream, businesses around the world increasingly look for ways to use these massive amounts of data to gain new insights
The job responsibilities of a data scientist are different across business domains even, varying from company to company within sectors. In general, though, the data scientist's role is to collate, analyze data through ML, deep learning algorithm models the multiple data streams both live streaming and historical sources offer a challenge. Data Scientists turn the model recommendations to gain competitive advantage or solve a pressing business problem.
It can be widely accepted that today's data science job goes far beyond simply collecting and reporting on data sources. Data scientists must be able to tell what the data wants to communicate to the business in ways that the C-Suite can understand, rely and act on.
To begin with, Data Scientists must be up-to-date with AI, ML, Statistics and Advance Excel skills and possess technical skills and non-technical skills. This holds true for data science profession enthusiasts and data science experts. They must-
• Learn statistics, probability and mathematical analysis. Some of the important topics being Descriptive and Inferential Statistics, Linear Algebra, Calculus, Discrete Math, and Optimization Theory.
• Have a good knowledge of programming language. Data Scientists must be skilled at least one programming language. Some of the essential programming languages and tools for Data Scientists include Python, which the first choice because of its code-readability, scalability and versatility. R is also widely adopted by data scientists offering an intensive environment for data scientists to analyze, process, transform and visualize information.
Analytics Insights estimates that Data scientists who have AI capabilities will command the highest salary packages across India, the US, Canada and the UK. As analyzed from the below table-
In a crux, we can safely say that the Data Scientist role has taken the world by storm. Today, as more and more organizations are using Data Science to improve their business efficiency, products, business decisions, and marketing effectiveness undergo a drastic transformation. Besides, Data Science capabilities have made various business processes efficient, error-free and more trustworthy for the organizations and businesses.
