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Data Science is Becoming the Most Important Skill in Fintech
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Data Science is Becoming the Most Important Skill in Fintech

Data Science is Becoming the Most Important Skill in Fintech

Peter Renton·
Peer to Peer Lending
·Nov. 30, 2017·2 min read

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.

Chris Skinner penned this interesting piece last week claiming the critical importance of data in banking:

Data is the new air, and the banks that breathe the best will win. In other words, banks that really get data analytics, and can apply machine learning to gain deep customer insights are the ones that will survive.

Basically what Chris is saying is that the banks with the best data scientists will win. There is so much data today – from mobile phone usage, social network activities, web browsing, credit card transactions, payroll, email, biometric data, behavioral data and much more. Now, privacy is clearly an issue with some of this data and companies need to make sure they are adhering to all consumer protection regulations. Even so, the amount of useful data that is actionable is only going to get bigger.

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 fintech 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 50 Best Jobs in America 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 fintech company should be building their data science team. It is no longer optional.

  • Peter Renton
    Peter Renton

    Peter Renton cofounded Fintech Nexus as the world’s largest digital media company focused on fintech before it was acquired by Command. Peter has been writing about fintech since 2010 and he is the author and creator of the Fintech One-on-One Podcast, the first and longest-running fintech interview series.

    View all posts
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artificial intelligencebig datadata science
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