How is the data science job market beaming with opportunities?
Ever since data-fueled digital disruption, data scientists are always on demand. In a business setting, data scientist’s roles and responsibilities include predicting potential trends, exploring disparate and disconnected data sources, and finding better ways to analyze information. They excavate through large amounts of structured and unstructured data to identify patterns that can help discover new market opportunities, boost efficiencies and more. They also carry data mining by using APIs or building ETL pipelines, data cleaning using programming languages like R or Python. Because of the capabilities of data scientists, they are paid lucrative salaries by their organizations. This is why data scientist is deemed as sexist jobs of the 21st century. In a recent survey conducted by Analytics Insight, by 2021, there will be 3,037,809 new job openings in data science, worldwide.
With the increasing number of unique companies posting for data science job roles, it clearly indicates that data is a popular job openings aggregator. Further, these companies treat data as an unbiased, random sample of the market. According to Analytics Insight, the global market of Big Data is forecast to grow at a CAGR of 10.9% from US$179.6 billion in 2019 to US$301.5 billion in 2023. Simultaneously Big data market funding will rise to US$4.5 billion by 2023 from US$2.7 billion in 2019 with a CAGR of 13.5% in the same period.
Capturing, interpreting and being informed by data can radically transform any organization. This is why several industrial niches are looking to hire data science experts who help transform their business trajectories. More increased usage of data, will lead to better data maturity. Top industries include, BFSI, government institutions, healthcare, manufacturing, retail and IT.
It is important to note that these data science job roles are not limited to data scientists. It also includes other fastest-growing job positions like data analyst, statistician, data engineer/architect, machine learning engineer, big data engineer, business analyst, information security analyst and management information system (MIS) reporting executive. Analytics Insight believes there will also be broader diversification of roles in data science over the next year, with the emergence of hyper-automation, software robotics, RPA, virtual agents and chatbots and ML-based decision management.
Besides, given the COVID-19 pandemic scenario, while most of the job profiles faltered due to the economic downturn, the data science industry managed to pull through successfully: compared to other tech jobs profiles, data science had comparatively fewer lay-offs, salary cuts and furloughs. This is primarily because most of the employees in data science domain still have access to tools and resources required to perform assigned tasks, even amid work from home situations. Besides, firms and enterprises and institutions need data scientists to help mine critical insights from vast troves of data generated today.
On the basis of data science skilling, MapReduce, Apache Pig, Machine Learning, Apache Hive and Apache Hadoop will be the most in-demand skill in this job market. In terms of coding skills, Python will continue dominating the most preferred programming language, followed by R, SQL, MATLAB and Java.