 Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at the Chief Data Sciences USA Conference in downtown San Francisco, talking to all the smart people, trying to get the best stuff we can get for you. There's a lot of data scientists and practitioners here. We're excited to have Masad Sheikh on the head of Enterprise Data Science for CUNA Mutual. Welcome. Thank you, Jeff. Absolutely, so you are talking here about what it's actually like to be a Chief Data Scientist, not the paper, not the job description, really kind of what it is you do day to day. Yeah, exactly. This is one of the topics I'll be talking, discussing this afternoon. So it's about what exactly is a data science? You know, there's a lot of confusion, like is data science a new name for analytics? Or is it advanced analytics, or what it is? So that's, I'll begin my conversation with what is a data science in a real world, how it looks like, and talking about two case studies. One is focused on the customer experience, and the next one is on the revenue growth by doing some analytics on the customer, like real-time analytics. And also, you got to be a sales guy. I mean, that's what came up in one of the earlier panels, is that to be successful, you have to sell the value of what you have into your business units and how you can help them do a better job. Yeah, I think like for a data science group to be successful, you need to have like a 50% sales skills. I would say like sales, marketing, these are essential, I think. These are the foundation for you to be successful in addition to doing your actual job. Yeah, because the main reason here is earlier it was IT and the business. If you just go back a few years, there wasn't a centralized data teams. They were not there earlier, right? So IT was addressing most of the data issues and the business was doing. So now, all the organizations, they realized, you know, like how can we really derive the more value from the data? So they started centralizing the data teams. So that's a new role and the new group itself. So the first thing is, it's more about like, as you said, sales and marketing, you need to market yourself because you're new in this, any organization you take it. So first market yourself. Tell what exactly you offer, how it is different from earlier. So yeah, that's a marketing and sales speech. And again, like so, what exactly means? How do you help them grow their revenues? How do you help manage the risk better than the past? And how do you help achieve the operational efficiency? In a nutshell, so probably it's more about how do you meet, how can we help you meet the corporate and the business area goals using data science? Right, it was interesting. It came up on the earlier panels today that it was really, you know, asking the customers, what do you need help with? How can I help you get through your day to day job better? Not really giant strategic initiatives, but really tactical things, so that then you can bring the power of data science to bear to help them solve their problems and move their objectives forward. Yeah, there are two folds to it. Okay, so one is definitely completely agree with you. Okay, one is we need to offer and help wherever it is needed. I'm afraid if that is the only case, we'll end up in a situation of just supporting, helping, making them more efficient, but where the industry is evolving today is not in that area much, okay? So the way the industry is leveraging the data science today that we can see like in the past five years, a lot of organizations like, yes, everybody knows what name I'm going to take, Uber, okay? So we saw this morning. So Uber, they don't own any cars, okay? But they're the world's largest taxi company, right? Similarly. So that is the thing. So this is the breakthrough, okay? These are the organizations using the data science to evolve completely. So it's not just supporting and helping people to be more efficient. It's to show that, okay, how can we discover new products for you? Right, right. Okay, how can we research what competitors are doing? Can we do better than them? How can we help grow revenues? Okay, it's not just supporting. I think that is where the data science has a real edge over what we are doing in the past versus now. Right, yeah. So has Uber in, you said CUNY Mutual's been around for 80 years, 4,000 people, mature business, mature market, is your management afraid of the Uber of your world? I mean, has that sunk into them? Because Uber was not just another taxi company. It wasn't the green taxi company taken on the yellow taxi company. Airbnb was not Hilton taken on Hyatt, taken on the Western. I mean, they fundamentally changed the business based on using data, mobile applications, and really reassembling things in a new way. Does your management, and I don't want to pick on your company specifically, but within your industry, do they see the potential of that happening to them? And are they using you to try to fend that off or look for, as you said, kind of more proactive ways to get ahead of that curve? Yeah, exactly. So this is where is the concern across the industry, especially the financial industry. So Uber is in the taxi space, but there are some organizations within the financial industry, like Lending Club, to name it. And there's one more, they are in the conference, they recently started, it's a film tag. There's a bunch of those, right? Yeah, there are a bunch of those. And we can see the way they are growing the business and they're competing with larger banks, like Bank of America, Chase, and everything. So it's everybody, like even if you see one of the largest banks in the world, they realize it's going to be a threat. They started their own film tag. I don't want to give the name. One of the largest banks, who has the largest presence in the world, they started a new company known as Affintech. So this is where they are also thinking, so let's be ready for this competition. So it's not far, the one of the fear, I don't say like a fear, but one of the concern for these organizations, it's not far when Amazon and Google, will start introducing, they already started. So capturing this market. So how can we stay ahead of them or at least compete with them? I think this is a concern across the industry. And has your management, again, not to pick on your company specifically, but within the industry and or your management, kind of come to the realization that they need to bring you to the table in a proactive new services way, as opposed to just wringing out extra efficiency, right? Because you can't save your way to growth, right? That's an age rule. Yeah, exactly. So just going back to my experience in the same field, being a chief data scientist at other banks, I was there. So the goals were different earlier, okay? Most of my time spent was on the risk management, doing the analytics to manage the risk better. But now what I can see, the trend has changed. I said, okay, give, no, risk is very important to the banks and the insurance industries and credit unions. But the way they are transforming their strategy is focused on generate more revenues, either using the current process or introduce the new products or the new business lines. And use the data science to do that one. I can see a lot of organizations, they realize it, they're very open for this change. And this is happening today. Good, yeah. So before I let you go running low on time, impressions of the show, since you've been here for a couple of days. Any surprises, you know, how's it been, kind of being with your peer group in this situation? I think it's fantastic. You know, like so, the biggest thing is the networking. We, I get to meet the people from the different industry sectors with a similar background in the data science, understanding how they are doing, what they are doing in the data science field and sharing my perspective with them. So it's a fabulous event, I would say like. So it really connects the people with similar thoughts. Okay, in a different areas, you know, like somebody's trying in the healthcare, I'm in the financial industry. So try to understand how they are trying to grow their business using the data science versus, you know, it really gives an opportunity for us to connect with the people. So it's really a great event. Yeah, as opposed to going to like, you know, kind of your typical industry shows which probably have a data science track, but you don't quite get that cross industry pollination if you will. Yeah, exactly. All right, super. Well, Saad, thanks for taking a few minutes out of your busy day. Good luck with your panels later this afternoon. Yep, thank you very much. Absolutely. I'm Jeff Frick, you're watching theCUBE. Thanks for watching.