The Future of Data Scientist

Posted by minati biswal on April 24th, 2019

Data science is a constantly evolving beast, and any data scientist who wants to stand a chance of keeping up-to-date with the state of the industry needs to be keeping a close eye on all recent developments and following along with their peers.

Use and Demand of Data Science

As AI and ML become mainstream, a new breed of security data scientists will emerge in 2019: AI and ML techniques are data dependent. Preparing, processing, and interpreting data require data scientists to be polymath. They need to know computer science, data science, and above all, need to have domain expertise to be able to tell bad data from good data and bad results from good results. What we have already begun seeing is the need for security experts who understand data science and computer science to be able to first make sense of the security data available to us today.

Data science benefits both companies and consumers alike. McKinsey Global Institute found that big data can increase a retailer’s profit margin by 60 percent, and “services enabled by personal-location data can allow consumers to capture 0 billion in economic surplus,” meaning they are able to purchase a good or service for less than they were expecting. For example, if you budgeted ,500 to purchase a jacuzzi and then found the exact model you wanted for ,000, your economic surplus would be ,500. Data science can simultaneously increase retailer profitability and save consumers money, which is a win-win for a healthy economy.

Along with statistical and machine learning modeling using Python or R, Feyzi Bagirov, data science adviser at San Francisco-based B2B data insight vendor Metadata.io, said he's also seeing more demand for skills in SQL, NoSQL databases, Apache Spark and relational database management systems (RDBMS). 

Data Science Is Helping the Future

Data science can improve public health through wearable trackers that motivate individuals to adopt healthier habits and can alert people to potentially critical health issues. Data can also improve diagnostic accuracy, accelerate finding cures for specific diseases, or even stop the spread of a virus. When the Ebola virus outbreak hit West Africa in 2014, scientists were able to track the spread of the disease and predict the areas most vulnerable to the illness. This data helped health officials get in front of the outbreak and prevent it from becoming a worldwide epidemic. Get in depth knowledge from data sceince online course.

Data science has critical applications across most industries. For example, data is used by farmers for efficient food growth and delivery, by food suppliers to cut down on food waste, and by nonprofit organizations to boost fundraising efforts and predict funding needs.

In-Demand Data Science Careers
Data science experts are needed in virtually every job sector—not just in technology. In fact, the five biggest tech companies—Google, Amazon, Apple, Microsoft, and Facebook—only employ one half of one percent of U.S. employees. However—in order to break into these high-paying, in-demand roles—an advanced Data sceince ceretifcation education is generally required.

Data scientists are highly educated–88 percent have at least a master’s degree and 46 percent have PhDs–and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist.

In 2019, we see the demand for data science pipeline platforms increasing dramatically. We often compare data science to the software development boom.