What's a Data Scientist?
Posted by Steve Stovall, AVP, Credit Union Resources, Inc on 3/15/2018
By Chris Nicholas - CUNA Mutual Group
 
A little while ago, I was giving a talk on predictive analytics, and a young professional in the audience interrupted me: “What exactly is a data scientist, anyway?” he asked. 

Given the number of people who suddenly perked up to hear the answer, I realized he wasn’t the only one in the dark. If you’re wondering, too, allow me to shine a little light science on the topic.
As the Chief Analytics Officer of AdvantEdge Analytics, I direct some very smart people who are busy conducting data science for credit unions. Let’s start there. Data science is the process of extracting meaningful patterns from large sets of data. These days, data science has proven important to all businesses, including credit unions. This is because it employs reliable methods of analyzing data, discovering trends and identifying business insights.
To be sure, many analysts are involved in similar activities, but a data scientist is, naturally, diving deeper into the data. In many ways, the data scientist spans the gap between IT and the business. For most analysts, the data has already been prepared for them, whereas data scientists discover data in the systems themselves. They extract it, transform it and identify connections.  
While working with the data is part of data scientists’ activities, they also take that exploratory analysis one step further. They codify and predict the outcomes of the information they are studying. They constantly search for opportunities to build repeatable, technical assets that we call predictive models 
Predictive models are where the greatest business value lies for the credit union. It’s one thing to use data to understand what’s been happening in the business. But, it is quite another to use data to make accurate predictions of future outcomes. Once these models are created, business areas can use the information to support actions like building marketing campaigns or creating specific business initiatives.
For example, let’s say you’re the credit union: You want to predict which members are likely to churn from your portfolio and isolate the causes for leaving. Predictive models allow you to do that. What’s more, they can help you identify the appropriate actions and programs that can help you retain those members. And, they provide the means to measure the success of the programs.  
So, a data scientist is a multidisciplinary expert with deep skills in mathematics, computer science, statistics and computer programming. In my role, I am always looking out for well-rounded data scientists. They typically must possess a great deal of business acumen to go with their technical expertise. They also need to have strong communication skills because they operate at so many different levels of the business. In my experience in the trade, it's typically a small cohort of experts that fit the bill.
Unfortunately, it’s not very likely that a credit union has the resources to employ a full-time team of first-rate data scientists. The good news is that there are now options in the marketplace. If you're looking to capitalize on the value that data science can create for your organization, take a look at industry partners like AdvantEdge Analytics. We have a full complement of data scientists on staff, with the processes, practices and experience to help deliver the full power of data science to your organization. 
Originally posted on the CUNA Mutual Group Insights blog on Wednesday, March 14.
Categories: Business Partners, Financial & Auditing, Marketing & Printing, Research, Sales & Service, Strategic Planning & Consulting
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