Way back in 2012, the Harvard Business Review (HBR) described ‘data scientist’ as “the sexiest job of the 21st century”. The title could be disputed, but the epithets for the job are many – it continues to be in high demand, is a challenging career with lots of learning opportunities, and offers high salaries.
What is the job of someone in data science?
A data science professional essentially works on a mix of computer science, mathematics, and statistics. In this age of big data, huge amounts of data are flowing into organizations of all sizes and in all verticals. The data is of diverse nature of the data and its size is ever rising, and it could be mined to reveal potentially very useful insights that guide an organization in the pursuit of its strategic goals. This is the task falling to a data scientist, who must collect, organize, and analyze the data to deal with the process, strategy, and other questions in all kinds of enterprises.
Why is this an attractive field?
As discussed earlier, a data science career is an attractive choice for professionals looking to make their mark in the world of business. It involves an interesting, challenging, and stimulating mix of business knowledge, statistics, and technology. There is a whole world of niches and possibilities within data science, which adds to its charm.
What are the pros of working in data science?
Excellent job prospects
Data science received a score of 9/10 from LinkedIn on career advancement, implying high prospects of moving up to more senior roles fast. According to the US Bureau of Labor Statistics, the job growth rate from 2018-2028 for computer and information research scientists – which includes data scientists – far outstripped other groups at 16%. When overall jobs for analytics are considered, about 70% are for data scientists who have under five years of experience.
With an annual median base salary of USD 130,000, ‘data scientist’ was ranked as the most promising job of 2019 on LinkedIn. Even Glassdoor estimates the average salary at USD 113,309 annually. The role of a data science professional has a lot of prestige, given that it helps companies to take better, data-driven decisions.
A data science career is not limited to any one vertical. It also finds demand in a variety of industries, such as banking, healthcare, and marketing, among others. These factors imply numerous options when it comes to functions and industries where data science is required, as any data-driven decision-making process will need a data scientist.
Data science requires working on computer programming, mathematics, statistics, and strategy. Along with constantly evolving technology, this makes the work challenging and helps the person to keep learning new skills. It is not templatized work, so new ways must be found to tackle each problem.
What are the cons of working in data science?
There is no one definition for data science, meaning possibly unclear role descriptions in a data science career. Given that there can be extraction, sorting, analysis, and visualization of data, all of which combine to give strategic insights, the same role may require different combinations of these in different firms.
Tough to gain expertise in
Given the large amounts of data and its often-arbitrary nature, there is a lot of work to be done before useful results are obtained. The person will need expertise in technical skills as diverse as programming and data visualization, as well as many non-technical skills. Candidates can choose one of the top data science certifications to pick up the necessary skills.
The field is continuously evolving, which requires a data science professional to put in serious efforts to stay up to pace with the requisite skills and know-how in the field.
A generalist approach
Most data science projects do not require the person to work in too much depth in any one aspect of the business. The focus tends to be on solving one problem and then going to the next one. Specialization is difficult to gain.
Data ethics and privacy
A huge variety and amount of data are gathered and analyzed, and a lot of this could be sensitive data that must be handled with caution. The data science professional must ensure no breaches in privacy and must keep the data safe.
A data science career can get a great boost with a top data science certification. This shows the person is invested in continuous learning and has the requisite skills and knowledge to take on higher, challenging assignments.