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An article in Harvard business review once called being a data scientist “the sexiest job of the 21st century”. So what does it take to earn this title?
A data scientist can overcome multifaceted challenges through the use of data combined with machine learning approaches. On the other hand, Data Science as a course is a multidisciplinary field of study that combines computer science with statistical methodology and business skills. To qualify as a data scientist, they must have unique experience as well as expertise in the main parameters of data science. This may include statistical analysis, data visualization, use of machine learning methodology, understanding and assessing conceptual challenges related to business.
Envision the future
What does the ideal future look like for science? Science enthusiasts would likely envision a steady advance in technology over the next five years. Scientific and technological innovations are continually improving, new opportunities are created and newer techniques are opened up to improve the business operations of individuals and organizations.
Many organizations are looking at data science as the key to increasing their competitiveness. As a result, production has also improved in recent years. Take Apple and Amazon as examples. Both companies have improved their brand positioning globally, delivered stable profits and are poised to continue to grow, in part due to their high-end reliance on data science.
Related: Why the ‘Data Scientist’ Will Continue to Be ‘The Sexiest Job of the 21st Century’
We are constantly faced with unpredictable situations – like the Covid pandemic – which has called on companies to do everything possible to minimize human-to-human contact. Data science and the rapid evolution of technology have contributed to these changes and to prove that a bright future exists. This, however, will depend on the quality and extent of the data that organizations can acquire.
As the focus is more on data on consumer behavior, organizations are constantly looking for the best way to collect this information. In addition, more and more calls for ethics and legal compliance have been made across all sectors of the economy. This increases the need to use data science, ensuring that the data acquired is stored securely. Confidentiality is also of the utmost importance.
All of this emphasis on data science makes data scientists pretty crucial to businesses of all sizes. These professionals have the skills to develop machine learning frameworks and deliver value for the vast acquired datasets available to them.
Despite the growing use of AI, the demand for data scientists is expected to continue to increase. A data scientist usually dives into analyzes combined with results. AI is the key component of machine learning, which relies on the development of autonomous frameworks. This generates defined results that lack interactions. Additionally, AI looks at the aspect of a scalable framework as opposed to analytics. However, its value has yet to be explored in depth, and this may pose a challenge for the future of data scientists.
Related: Reasons Why Data Science Will Continue To Be The Most Desirable Job Of The Decade
But despite the expected setbacks for data scientists, various positive points should remain hopeful. One is the increased granularization of the roles of data scientists. The other is the increased need for expertise to reach unique areas of work and also to maintain competitiveness through the use of specialist knowledge. In the future, there will be greater opportunities to develop more advanced algorithms and push the field to showcase what data scientists can offer in the world of science and technology.