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Why Becoming a Data Scientist Should Be your Focus in 2021

March 07, 2021

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Why Becoming a Data Scientist Should Be your Focus in 2021

Data scientists have been positioned as one of the top three trending jobs in LinkedIn’s Emerging Jobs Report 2020.

The demand for talent in the field keeps accelerating as organizations look forward to becoming data-driven. Since then, it has been an upslope with an estimated 3,200 job openings every month. These job postings have been seen in all sectors and not just in the technology sector.

An IBM report predicts the demand for data science and analytics from 364,000 openings to 2,720,000 by the end of 2020. While we may not experience a dip in data science jobs amid COVID-19, it is likely to increase due to the pandemic. Also, based on a report by the U.S. Bureau of Labor Statistics, nearly 11.5 million jobs in the data science field will be created by 2026.

Therefore, data scientists have the potential to transform business trajectories and help make better business decisions. As we enter 2021, experts in data science are likely to work with data that have been stored in a cloud-based database, e.g. Google BigQuery. Professionals skilled in data science tools and technologies will be in high demand as we enter another year, 2021.

Below are the top reasons why becoming a data scientist should be your core focus –

The dearth of data science talent

Organizations are facing two types of talent deficit in data science. First, a data scientist who needs to perform analytics, and second, a data scientist who can understand data and tools used in the industry. Sadly, the supply of talent in these job titles are low while the demand is considerably high.

According to the report, “Investing in America’s Data Science and Analytics Talent: The Case for Action,” nearly 70 percent of employers in the U.S. will prefer job applicants with skills in data by 2021.

Whopping salary compensation

Given the demand for data science professionals, even salary compensation is lucrative. Data science is one of the top-paying industries in the technology field.

Based on Glassdoor’s report in February 2020, the base salary for data science professionals in the U.S. was US$113,000 per annum. In Australia, it was AU$114,000 per annum. While average salaries for data science graduates were recorded to be between the range of AU$90,000 and AU$200,000 and AU$40,000 – AU$60,000 for a business graduate.

No entry barrier for other professionals

Data science is not limited to computer science graduates or engineering graduates. Even professionals who hold a specialist in mathematics, statistics, economics, and social sciences can easily get into data science.

Professionals with no coding experience may face slight difficulty but can still manage through online training programs and certification programs.

Multi-faceted sectors

Every sector is in dire need of experts holding skills in data science. Life sciences and pharmaceuticals, food, and beverages, industrial goods, agricultural, and utilities are some of the sectors wherein you can start looking to start your data science career.

Focusing on the tech industry to find jobs may exclude many cool job roles for you. As long as you have the skills and experience working on different projects, you can choose any sector you like.

Companies are seeking experts to handle their data

Every company generates a large amount of data. This simply means that every company is sitting on large volumes without knowing what to do with the data. Therefore, they will need people to organize, analyze, and draw meaningful insights from such data.

Multiple job roles

Professionals skilled in data science belong to several disciplines – machine learning, mathematics, statistics, and data analysis. Therefore, finding a job role in the field is not limited. However, data scientist still stands to be the topmost demanded job titles in the industry. Most people lack presenting practical skills and this is one major reason why seeking jobs in data science has become challenging.

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