Why is career and data science and AI is in vogue?

Data Science, AI and ML
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One of the most popular developing disciplines and most sought-after employment possibilities is data science. According to a well known research, Data Science is the fastest-growing employment category, with a 37 percent increase in hiring over the last three years. Data Science is reshaping practically every business and getting momentum by the day. Everyone wants a piece of this cake then why should anyone stay behind.

New industry with varied opportunity

The majority of data science jobs are relatively new to the business did not exist five years ago. The potential for big data and its analysis to expand, from law to accounting to medical science and finance, is immense. Big data is continually changing in response to business objectives and data-centric project requirements. The new initiatives and divisions will need multi-skilled employees from many industries who have been trained in the newest big data technology. Many organizations are laying off employees owing to automation, while others hire massive data experts to develop new smart technologies. This tendency is growing year after year as companies learn how to use data to improve their operations, products, and strategy.

Changed career outlook

The ability to gather, manage, analyse, gain insight, and anticipate data is a skill that is in high demand across all sectors, verticals, and new innovative organizations today. More data experts are needed in the sector, and the talent is expected to come from a variety of professions and backgrounds. Because these individuals already have the expertise to use data-driven technology and processes, industries require experts to upskill in this area. This means that even if you don’t have experience in big data or analytics, you can shift into a data science profession.

Easy path to switch between sectors

As mentioned in the earlier point, the wings of data has encompassed various sectors alike. With the knowledge of data crunching and analysis, one can change field in any sector, namely enginering, consulting, business, accounting, finance, IT, science, etc.

Skills for changing the career path

-Capacity to code or willingness to learn – Python, SQL, R Data

-Visualization & Communication – showing data patterns clearly and understandably

-Problem-solving attitude – ability to develop data-driven solutions

-Experimentation Skills - the ability to execute tests, create experiments, and assess results

Even if you don’t have any technical skills, there are educational programs accessible for anyone interested in pursuing a career in data science or who want to improve their skills.

Age is just a number

When it comes to entering the data science and AI community, individuals willing to put in the effort to obtain the skills necessary to have a successful career in data science will find it to be inclusive and accepting. Regardless of age, the skills that most matter are domain expertise, desire to learn, application of new ideas and ability to think analytically and creatively. In other words, no one is ever too old to become a data scientist or to switch careers to data analytics. In fact, if you’re a more seasoned professional, your prior learned expertise mixed with your industry knowledge can help you stand out.