T
he digital revolution in technology has changed the whole
landscape of the data science industry. The demand for
big data, AI and other cutting-edge technologies are
surging in the market. With the growth of enormous datasets,
not only data science but data scientists are also expected to
evolve with time to meet the industry demand.What Could Be the Possible Evolutions in the Role of Data
Scientist?
Owing to the prevailing massive talent gap in data science,
data scientists have to try enough to master both technical
and business understanding of their projects. Currently, data
scientists have found themselves stuck in a situation where they
have to manage a broad range of data-specific work due to
the project demand which develops a lot of stress in them.
Therefore, companies are trying to include more skillsets in their
ecosystem including data science leaders, data translators,
and domain-specialist. This simply implies that there will be a
demand for data scientists with skill-specific roles.
Previously, the roles of data scientist used to range from data
capturing task to data insights. But the scenario now is different
and will continue to evolve with time. Today, the roles of these
professionals are much diversified than before. Operating and
managing big data requires a lot of expertise with different
skillsets. As more and more companies are realizing the need
for a shift, the demand for different data science skills is
expected to soar up over the next decade. And, there will be
more specialized work available for data scientists.The Upsurge in Data-Driven Strategies in Organisations
Today, data influences every aspect of an organization from
marketing to customer relations, from identifying threats and
weaknesses to form finance strategy. An incapacitated data
strategy can nearly kill a business.Therefore, more and more organizations are beginning to
realize the value of data science and are more focused on
developing data-driven strategies with high recruitment of data
science talents in the years ahead.
Every level of employees should participate in understanding
the type of data significant for their respective department
which would consequently help in building better strategies.AI-ML To Wing Up the Ambitions of Data Scientist
As the debate of human workforce vs digital workforce is
heated up in tech-industry, professionals are fearing of the
consequence of AI/ML adoption in organizations. People
are worried that technologies will outmode the work of data
scientists in a few years. There are certain companies that
believe that automation is way behind matching up the human
intuitions. These technologies are more likely to assist data
scientist in the data processing.
A huge volume of data is being generated daily and it has
been predicted by 2025, about 463 exabytes of data will be
generated globally. In reality, it is not data scientist’s cup of tea
to manage this huge sum of data alone. This is where AI will
be of significant help.
However, AI will not threaten their job as a number of
organizations believe that AI would eventually increase the
headcount in their ecosystem. Rather the technology would
tend to eliminate 80 percent of the workload of data scientist
occupied with repetitive and mundane tasks. Subsequently,
they will get more time to focus on innovation and efficiency.
As the current scenario predicts the data scientist will become
a vital investment over the next decade and the variety of
jobs lying under this category will become prominent roles in
a business environment. Additionally, the prevailing insights
suggest that data science provides a highly valuable edge to
an organization to thrive in the data-driven market.27
THE 10 MOST PROMINENT ANALYTICS AND
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