Role Of Data Science In Fintech

Role Of Data Science In Fintech

Data is everywhere. The world generates some 2.5 quintillion bytes of data every day. Some people have said we are drowning in data and that may well be true. But we are starting to get better at making sense of massive amounts of data. Which brings me to the point of this article. Data science is going to become, if it hasn’t already, the most important skill in fintech.

Before we go any further we should define what we mean by data science. There is no standard definition but I like how NYU describes it:

At its core, data science involves using automated methods to analyze massive amounts of data and to extract knowledge from them.

Extracting knowledge is the key point here. We may be drowning in data but a skilled data scientist will be able to extract the useful parts of this data and discard all the noise. With so much data available today in all industries, particularly in finance, those companies that can extract useful and actionable knowledge will be the winners. Regardless of how intelligent our systems become human beings need to build the tools as well as understand and take action on the data. Data scientists are going to be needed in many areas of fin-tech businesses such as customer acquisition, cybersecurity, customer service – even compliance. For online lending businesses, the other two critical areas are underwriting and collections. Glassdoor releases an annual report and for the second year in a row Data Scientist had the top spot. Why? High salaries and lots of job openings are the main reasons. IBM predicts that demand for data scientists will continue to outstrip supply for the next several years. Every fin-tech company should be building their data science team.


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