Data Scientists are one of the most-sought after talent today. And as clichéd as it may sound, their significance will grow steadily across industry, as companies increasingly become reliant on data-driven decision making. As the amount of data generated by companies, as predicted by IDC — ten folds increase in volume of data to 175 Zettabytes, 60 percent of which will be managed by businesses, these data wrangling professionals will garner ubiquitous presence.
While there’s a sunny side of the growing demand, there’s a dark side too. As companies sprint towards leveragingdata science to expand their data science capabilities and hire more data science professionals, aspirants will jump with excitement on this opportunity. However, will there be enough jobs? Is there a credible way for data science professionals to prove their worth?
What do Data Scientists do?
The major responsibility of a Data Scientist in an organization is to support leaders in their decision making. They collect data from complex business processes, analyze, find patterns, and make recommendations that deliver results.
To do so, they need an extensive set of skills –programming, machine learning, statistics, and visualizations. Data science demands a strong level of mastery in quantitative aptitude and numerical skills. Data science uses complex mathematical techniques and sophisticated algorithms to solve problems with available data.
Business acumen is important skill required among them. It helps to understand business problem, build hypotheses, derive conclusions and check the feasibility of recommended solutions. Further, iterate for possible better solutions to the proposed problem. They take decision making up multiple notches using their extensive skillset.
Communication skills is important for them. They are required to clearly communicate their findings and solutions to various stakeholders. Thus, they are required to have good communication skills.
Demand for Data Scientists will grow across the industry. Thus, there’s need for a uniform approach towards working in data science. In this scenario, it is important to set a standardized framework that qualifies data science professionals and also sets a code for best data science practices. Thus, the need for data science certifications comes to picture.
Moving towards certifications
It is widely known that the industry is facing shortage of data science professionals. To overcome this, industry is propagating data science education via numerous means. Collaboration and partnerships with leading higher educational institutions to prepare Data Scientists. Universities and colleges have come up with ‘micro degrees’ in data science.
Given the shortage of data science professionals, graduates and working professionals are reskilling themselves in data science skills. Inevitably, lack of talent is turning out a boon for these professionals who can equip themselves with in-demand skills and prepare for some best roles in the industry. In addition, companies have started offering in-depth boot camps to train and retain their own employees for future.
In addition, online learning platforms have also started offering short term courses for learning data science and gaining practical experience. These platforms offer short-term and long term courses which can further lead to data science certifications, providing more credibility to their specialized skills.
Over the past decade, data science has grown exponentially. It continues to do so. At the same time, it is also seeing a gap in demand and supply of talent. While it is an opportunity for people attracted by lucrative salaries in this field, it is also a challenge for working data science professionals to keep themselves away from getting redundant and bolster their position in the field. Like any other technology-related field data science too requires professionals to keep themselves abreast of the trend. Certifications are a reliable way to do so.