Over the past few years, Data Science has become a huge buzz word and data scientists are of huge demand and regarded as the hot job of the century. But now in this current situation of Covid-19 the field is beginning to lose its relevance.
With the resources being limited during this pandemic, companies and businesses are revisiting their strategies and have shifted their priorities. The IT sector has seen massive layoffs including data scientists. It has been said that the data science bubble has finally burst. Companies have seen this opportunity to reduce the compensation of data scientists which was escalating earlier. Now the focus of organizations are shifting to reducing cost and automating the business process, it is expected that the demand for this job might decline.
Earlier each company wanted to join the AI race and started hiring data scientists in large numbers and hence it created a data science bubble. But most of the companies didn’t know how this was going to help their business and add value to it. The fact that 90% of the work can be done using basic engineering tricks and manual decision trees. Data science only helps to make this improve from 90% to 95-99%.
Many suggest that data scientists as a separate skill set might find it difficult to cope up without having the required engineering skills. It is because organizations are switching towards cloud technologies recently where this model could be automated and lose its relevance. Rather than investing in models to predict something which data science does, there exist a lot of opportunities in other areas like the Natural Language Processing (NLP) in automatic document classification. This technology makes the whole process of document management faster and effective using Machine Learning and Artificial Intelligence. It is a valuable addition that is tangible to the management rather than the intangible value that the data science model generates or predicts in the future.
Businesses are now trying to align their strategies with the core values and structure their process by their strategies. In this scenario, Data Science is not considered an essential function and they might lose their jobs in their context.
