Speaker 2: (00:01) You're not good enough to be in this college. Please leave my house. It's been 20 something years since that. I will never forget that cause I cried that day. I didn't know what I was going to study. I was like, what the hell? I'm not cut out to be an engineer. I'm barely struggling with mathematics. Like I'm barely making it. That's where my professor was like, you just need to put more time in it. You need to like study harder and look at me now. I got a PhD in math. You know he was wrong. Speaker 3: (00:26) [inaudible] Speaker 3: (00:30) [inaudible] Speaker 1:(00:41) what's up everyone? Thank you so much for tuning in to the artists of data science podcast. My goal with this podcast is to share the stories and journeys of the thought leaders in data science, the artists who are creating value for our field, to the content they're creating, the work they're doing and the positive impact they're having within their organizations, industries, society, in the art of data science as a whole. I can't even begin to express how excited I am that you're joining me today. My name is Harpreet Sahota and I'll be your host as we talk to some of the most amazing people in data science. Today's episode is brought to you by data science dream job. If you're wondering what it takes to break into the field of data science, checkout DSdj.co//artists with the S or an invitation to a free webinar where we'll give you tips on how to land your first job in data science. Speaker 1: (01:33) I've also got a free open mastermind Slack community called the artists of data science loft that I encourage everyone listening to join. I'll make myself available to you for questions on all things data science and keep you posted on the [inaudible] open office hours that I'll be hosting our community. Check that out@artofdatascienceloftdotslack.com community is super important and I'm hoping you guys will join the community where we can keep each other motivated, keep each other in the loop on what's going on with our own journeys so that we can learn, grow and get better together. Let's ride this beat out into another awesome episode and don't forget to subscribe, follow like love rate and review the show. Speaker 3: (02:16) [inaudible]. Speaker 1: (02:32) Our guest today is a cross disciplinary expert who leverages his expertise in computational modeling and applied mathematics to solve tough business problems. He's a forward thinking team player Speaker 1: (02:43) who's strategic perspective, stellar deal making skill and dynamic communication style has led to the successful negotiation of numerous multimillion dollar contracts. He's earned a bachelor's in mathematics from university of Illinois at Chicago, a master's in mathematics from the university of Michigan and MBA from grand Canyon university. You can if that wasn't aggressive enough already. He's since gone on to earn a PhD in applied mathematics and computational neurosciences from Arizona state university with a dissertation titled a mathematical model of dopamine neurotransmission, decode stablish, a faculty volunteer run mathematics tutoring center at grand Canyon university in Phoenix, Arizona. That has helped improve course completion and retention rates. He's a writer and presenter of five technical reports and has been invited to 15 scientific lectures and poster presentations in Chile, Peru, and the United States garnering more than $100,000 in academic funding. Most recently he was invited to present at the Phoenix power platform world tour conference in December of 2019 he's worked in numerous academic roles at Arizona state university and grand Canyon university before entering the industry as an analyst at rasa development fund and eventually going on to start his own consulting firm, Esperanza analytics solutions, a company whose mission is to gather, process and evaluate public and private data to advance the understanding of nonprofits and small business communities. Speaker 1; (04:07) So please help me in welcoming our guest today, a man who has impacted the lives of thousands of students and continues to give back to the community. Dr. David Tello. David, I really appreciate you taking time on your schedule to speak with me today. You know, I typically ask my guests what brought them into data science and you know, we'll definitely get to that. But I think it's really important for anyone who's listening that you share your journey, how you got to where you are now. So you immigrated to Chicago from Peru in 1993 during a really tough economic time in your country and you ended up going to school where influences could have easily derailed you. Looking at, you know, where you are now and everything you accomplish. It's such an inspiring story. Could you talk to us about some of the hardships that you had to overcome during such a crucial transition time and how it's helped you in pursuit of all that you've accomplished today? Speaker 2: (04:56) So in Peru from 1975 to 1980 we suffer the same thing that I've been as well as suffering now, which is hyperinflation things away and crazy expensive. In 1992 the bank or my mother used to be a secretary actually close and we had to move with my grandparents. And at some point we were, or it was 14 of us living in a house or not even a house. It was an apartment to have four bedrooms. And I was a sleeping with a cousin and my grandpa, my grandfather in a single room. So that's when my mother told my father, you need to take them to the United States. My father was already in the United States and she was referring to my sister and I. And so we came to Chicago and you know, as immigrants we think that everybody in the United States were rich, right? Yeah. And United States. But when I got here to Chicago, my dad was renting a single one bedroom and the bedroom was taken by my sister and it was my father and I sleeping in the living room. Speaker 2: (05:53) Two beds, two separate beds. We only have a few pots, four chairs and a table. That was Dallas. I started the United States. Speaker 1: So how did you, how did you kind of develop and cultivate your interest in mathematics and then ultimately data science? Speaker 2 I went to school and I always like numbers, right? You know, so, but it was difficult expressing myself in English to the Lord or whatever you want to call it. Luck that I never get in, get into gangs or anything like that. I graduated high school. I went to the newest student in Chicago because I didn't speak that much of English. I got placed in probation, but I met this professor, a Chilean professor. She was like, I'll teach you math. You just need to try and work hard. It's just like you said at the beginning of today, you know, I worked my tough to learn mathematics. Mathematics literally turned my life Speaker 1: (06:39) It's the language of the universe, right? It's the universal language. I have this saying, I'm married to knowledge and mathematics as my best man. So, so I read in your post the story of my American dream that you met a professor from the university of Chicago that said to you, it's clear that your first derivative is positive. The question is, is are secondary derivative positive? And when I read that then I'm like, you know, my eyes started welling up and I got goosebumps cause it's profound on so many levels. Can you talk to us about what your interpretation of that meant and why that quote has stuck with you for all these years? Speaker 2: That's actually two quotes and I'll tell you the second one when after I tell you started this one. So when I started at UIC, like I say, my first three semester went okay. Speaker 2: (07:24) But by the end of the third semester I was placing academic probation because I came from a school that most people were glad that they graduated alive. Then they graduated with this grades, right? The best student in high school, graduating with a 30 in the ACT my year. And I think that record still stands and I only had asked 17 throughout my bachelor's I struggle a lot. But then slowly I improved improving. Like I told you, my professor taught me and then by the end I was, when I was graduating with my bachelors, that's when I decided to go to grad school. And that's when I ha I had done a research at the university of Iowa and the men that I did research with wrote a letter of for me and he gave it to me and he happened to be a coauthor or the professor and Chicago, the university of Chicago was just a couple of miles away from where I went to school. Speaker 2: (08:23) I emailed him and asked for a meeting and I went to him and say, look, I'm thinking of applying here to Chicago, but it's $50 application plus blah blah blah. You know, I'd rather you tell me here now where it makes sense for me to apply. So here's my letter of recommendation, share my official transcripts. You tell me whether I'll cut it up or now she was at director of grad school at that time. She saw my grades was not impressed at all. I mean, I graduated with the same class average and they hear, read the letter of recommendation and I can tell that he was like confused because my grades say one thing, but I'm pretty sure that another recommendation says something somewhat impressive because when I did my summer research, I worked my tail off to be the best that summer. That's probably why he say, look, it's clear that you're, you gotten better with time, right? Speaker 2: (09:14) I mean, let's just explain to people what it means to have a first derivative a positive and a second positive or negative. There's only two outcomes on that curve. You're either going like he slowly and you're going up and you keep going out forever. Or are you going like lower right? You keep, you go out really fast, but then you getting the snow with us, solar as lower. I couldn't tell you myself which one was going to be, I didn't know that I got better with time, but had I been in his shoes, I'm not sure if I would have said the same thing, but he clearly, you know, at least for the university of Chicago, I can guarantee you I was not ready for that program. So he did me a favor by telling me that because when I walked out of his office, I knew I was not cut out to, to, you know, send the application and get a rejection letter. he told me, I'll let you get like a a hundred on the sat math subject for the GRE. Speaker 2: (10:09) But I know that of course that was, I was told, Oh my fifth sixth semester of UIC, when, when I was getting out of probation that you're going to love was at that time I was taking calculus two or three with my engineering friends and I saw that they were not, you know, they were smarter than I was. They weren't as good as Iowa. So when I heard that they were going to get jobs where they paid sixty thousand seventy thousand dollars and I was like, what can I get that same job? Right. I applied to in January., I wanted to apply to engineering. I went to talk to the engineering college and a man there that I won't tell you who his name was. His same is told me he just took freshman biology and took linear algebra. You got to be in an algebra but you fail freshman biology. Speaker 2: (10:57) I was like, super happy, super proud. It's like, yeah, I understand in algebra, but I just don't get biology. I thought it was a good thing. After he repeated four, three times, I realized he's not thinking this is good and she's actually thinking is bad. After that, he told me, you're not good enough to be in this college. It's been 20 something years since that. I will never forget that because I cry that day. I didn't know what I was going to study. I was like, what the hell? I'm not cut out to be an engineer. I'm barely struggling with mathematics. Like I'm barely making it. That's when my professor was like, you just need to put more time in it. You need to like study harder and look at me now. I got a PhD in math. You know he was wrong Speaker 1: That's powerful man. That's so powerful. Yeah man. Cool. Okay. You got chills going on right now, man. Wow. So you also said something that really stuck out to me that's been very powerful. Speaker 1: (11:54) Like you said, that being in Michigan taught you that you need to be around mathematicians that looked like you. I think that's a real powerful statement and I absolutely love it. Uh, cause in many ways as, as a data scientist, you're a minority because the field is filled with so many people who look like me, Indian and Asian. Uh, so would you mind talking to us a little bit about what it's like to be a minority in this field and if you have any advice for anyone that's facing similar challenges today? Speaker 2: (12:24) So to me, being a minority in the fields of data scientist is different than he was being a minority in the field of mathematics. And the big differences today. I'm a grown man and back then, you know, growing up in the city of Chicago in the 1990s everybody wanted to be Michael Jordan and a though like you want to fly like Michael, right? Yeah. And that's when you started developing in noticing that you want to be what you are actually looking at. Yeah. When I went to UIC and I saw the people in the math department, there was one Latino professor, which was a Chilean guy and I was one black professor who was also a system Dean and a cultural era arts and then you know they were stronger. They were one of each. Our department, there was like 80 70 people. Yeah. When I went to Michigan there was a few of them that you know were called a professor to say that, you know, not disrespectfully, but you know. Speaker 2: (13:35) Yeah. There were some professor were colored and they were a few people that they didn't care about race and they treated, treated me really nice. But in the entire city, the only place where I felt comfortable that I spoke Spanish was at a burrito place across the street from the math department. I don't know if it's still there. It was called Pancheros and I felt comfortable with the people that clean the, that uh, the offices, you know, to me that was like I learned with the years that he wasn't about race, not at all. It was about social economics. I came from nothing and the professors that I was, you know, interacting with, they had everything if you want to say. And when I made the PO, the professors, that minority professors that I met, I realize this folks also came from nothing. So that's what I actually came to understand what it was like as I had nothing to do with race. Speaker 2: (14:31) It has everything to do that. They came from nothing. They built itself into somethings. They became great names in the fields and look at them. Nobody judges them. Now in, in data science, I don't feel like I'm minority even when somebody, and I know a lot of people who are better programmers than I am. When somebody comes in, try to disrespect me. Quote or unquote. I know what I'm able to do and I know that I might not be able to go the logistic regression right now really fast and Python, but let's just talk about the register regression. I can guarantee you I can go toe to toe with whoever wants to do it. My skills are so much better than I was when I was 20 years ago. I don't feel I minority like whatever kid wants to get into data science. Just do it and find somebody that will be willing to coach you. That guy told you the beginning. You're a great example. When we go to DSD J you're there, you open, you answer questions. You're your peer to, what's her name? That is in San Francisco. Great resource. She actually helped me to get to be in the job that I'm currently. Speaker 1: (15:53) Are you an aspiring data scientist struggling to break into the field or then checkout DSD J. Dot. Co forward slash artists to reserve your spot for a free informational webinar on how you can break into the field that's going to be filled with amazing tips that are specifically designed to help you land your first job. Check it out. DSDJ.Co//artists. Speaker 2: (16:20) I, I, right now I'm working for the federal home loan bank of Topeka and I'm not sure if the audience knows that what is the federal home loan bank, but the federal home loan bank, the system was created by the U S Congress in 1932 so this is one of the most elite, elite prestigious banking institutions that you can find in the United States. And it was really hard to get a job here and um, have no idea how, how proud, how beautiful I was the night that I arrived here that I was like, I'm actually going to be working on this bank tomorrow at 8:30 AM Speaker 1: (16:51) Oh man. Yeah. I mean there's nothing can compare to achieving your goal. Nothing can compare to achieving your dream mass. I hit, I can imagine how astatic you were. And I mean it's just a Testament to all the hard work that you've put in to get to where you are. I mean, it's such an inspiring story, right? Just having a kid that just has a love of mathematics and then going to reach out to professors that are saying you might not have what it takes to eventually getting a PhD in mathematics, but it's not like it was easy for you to get your PhD. Right. And I saw your post on LinkedIn about that experience you went through for your qualifying exam. Can you kind of recount that story for us here if you don't mind. And you know, what has that taught you about yourself? Speaker 2: (17:33) I fail the qualifiers exams more times that I can count you being in grad school, you know what it's like within the first two in years. You gotta prove yourself. And now that I've been a professor, now that I'm out in the field of industry, I can tell you from a personal perspective, asking a student to warm it knowledge in two hours. This is stupid. It doesn't tell you anything about where they're going to be able to graduate or when I took those exams, I studied study. The first few times I fail. I fail. Every time I fail. I was ready to pack up and go back to Chicago. I was here in Arizona. I was ready to pack up and go back to Chicago. I mean, I actually recall a one one time Chicago, that's right before the statistics examine telling me her friends, I'm not going back. Speaker 2: (18:22) I'm actually probably going to go cancel my ticket tomorrow. And they're like, no, you have to go back. You let the only one of us that left UIC graduated went to grad school. If Kisco, she keeps pushing in this disclose of getting this PhD. You're not allowed to stay here. You get your ass back in that plane and give back and pass that exam. No other friend of mine that, she's a professor at community college right now. I remember very clear that year the movie Rocky Balboa came out. You know that is seeing where, where the rock is talking to his son and saying, it's not about how many times you get hit Right? It's how many times he can get hit, get thrown on the floor, get your ass back, duster up and get back and got goddamn brain life will teach you more than any classroom will do. Speaker 2: (19:16) And I have experienced probably the most painful life experience, which was the loss of my mother three years. And it didn't throw me to the floor, you know, almost did, but he didn't. Speaker 1: That's, that's powerful. So the night before your PhD qualifying power goes out, can you talk to us about that? Speaker 2: So I don't know if you've ever been in Phoenix, Arizona during the summer. Speaker 1: I've been there once in the summer. That shit is not pleasant. Speaker 2: And I mean Phoenix, Arizona King get as hot as 120 degrees and the night is not forgiving either. We're talking about a hundred degrees, a hundred degrees indoors. Now I'm trying to study it. I, the exam was going to be at the beginning of the semester and the semester started sometimes July. And I was on that for giving him months. Oh, I'm studying. And then the bar was, uh, I called my, my super, I'm like, Hey look, I got a test, you know, I got, this is hard. Speaker 2: (20:19) Sorry. Right. It's the weekend. I cannot go fix it. You know, you've to go so fast. And also I went and got some fence, ran the fence, keep studying on sweating, like dripping sweat on the papers and try and sell some integral. So I called my friend who lived like two miles away or not better, you know, apartment comes into tonight, did it. And I was like, Judah, the exam is tomorrow. I can't think with so much. She says, I just bring your sleeping bag. Comb-over you can study here in the living room. And you should have started the late, you know, you're welcome to crash here and then go to the exam right away because the exam was like midday or something. So I did, I went and I studied study, working problems, working problems, you know, and then I just crashed and got up and ran to the test. Speaker 1: (21:09) The rest of history, huh? Speaker 2 The rest was history. Speaker 1 So inspiring man. Now let's get into the, into the, into the present now man. So let's, let's get into Esperanza analytics solutions. You know, what's the inspiration for starting the company? What's the company all about? Can you talk to us a bit about that? Speaker 2: So when I started the company, I recently had resigned for rest of the development of fun. I, when I resigned for resident about, I'm fine at that point I met my friend now business partner, Mark R. Bauer. He actually was, he's an instructor in a company called thankful and he helped me start getting more acquainted with Python and gave me a list of videos to work on and used to be my resource for, you know, I, I, I kept thinking, okay, so I need to make money and I need to keep studying Python. Speaker 2: (21:56) So what do I do? Right. I learned through my previous job that it's not that hard to make an LLC. You only need $85, you know, with an $85 you put yourself with an LLC, you have your own company, now you're on your balls. Now the hard thing about getting an LLC is now you've got to find it. So when I did that, I set up the company and everything and the goal was to try to each people you know, or teach, uh, nonprofits in small businesses, the power of their own data. You give me your data and I analyze it for you and then I'll show you how to make more revenue based on what your data is saying. However, as you and I know, and not everybody understands the power of data right now, it's very, especially those who are not programmers or don't have a analytical background. Speaker 2: (22:50) So we try for a little bit of time in, as things kept going, keep going. You know, I have my bank account and started going down, going down. And when I reach a trace for, you know, my wife was like very supporting until we started to reach that threshold. You know, it might be time for you to start applying for a job because if you cannot make the company come up, you know, then I need you to, I need you to provide for us. Right. That's how I started at Fred's job. And then I ended up here in the bank. I mean, the name of the company came actually because my mom's middle name was Esperanza and my daughter's that, her name is just Bonanza. Mispronounce that means hope, you know? That's what I brought in is my, my, my flagship. I live with hope because if I didn't have hope, trust me, I would've been all over and done many years ago. Speaker 1: I mean, I read through some of the letters that your students have written to on recent LinkedIn Speaker 1: (23:46) posts, the orders not in your time as a lecturer. You've impacted thousands of students. So what advice do you have for any student out there who's struggling with the learning and upskilling that's required to become a data scientist? Speaker 2: (23:58) The man that you see in front of you has add and is this is dyslexic, which is probably not the things that you was begging somebody who has a PhD in mathematics. A lot of people will say that they don't go together just as I you say my, you know my days, at least when I was young, you know, my days were six, 15 hours long days off. I get up, I eat breakfast, I study until I drop date of the entire, I have gone 24 hours, 30 hours. I think the longest day per se that I win. It's like 50 something hours where I just drank a power drink, kept going, you know, kept going, keep going, go and like pour everything out in the computer on the books or keep going, keep going. And I don't consider myself as smart at all. Believe me, I know people that are 10 times as smarter than I am, but I have reach a lot farther than a lot of people because I didn't give up. Speaker 2: (24:59) I kept going, I kept going no matter how tire. How you, how difficult. My African American professor from UIC once told me that he two failed PhD exams and now he's the very last one. He was a student at Purdue in the 60s and you know that Purdue is a mainly Caucasian, white Caucasian town. In the very last one he was told either pass exam or get out. She went and read his book cover to cover every single problem. He saw the, he passed the exam. He became a professor where I went into undergrad. I had to do sometimes the same thing. You read the damn book cover the cover no matter why, solve every single problem if you have to. A lot of people want to have this big job, dream job of 100,000 I want that for everybody, but chase it like, you want something that it's a nice well reward. Be willing to put the hard work. Speaker 1: (25:59) What's up artists? Check out our free open mastermind Slack channel, the artists of data science loft at art of data science, loft.slack.com I'll keep you posted on the biweekly open office hours that I'll be hosting and it's a great environment and community for all of us to talk all things, data science. We look forward to seeing you there. Speaker 1: (26:26) One last question before we jump into the lightning round. There's already so much here that people can learn from your journey. This question might seem a bit redundant, but what's the one thing you want people to learn from your story? Speaker 2: (26:37) If you are an immigrant or even if you were born here in the United States in rural United States, the American dream is still 100% possible. It's all about all of alternatives, all about decisions and all about opportunities. By now I know better that poverty, it's all around. Any doesn't disagree with me. I know people have different shapes, colors, and backgrounds that are poor. I'm talking not even $10 an hour job. As I know by now I can sit in a table and break bread with somebody who's extremely poor and be really happy and be grateful that we are sharing bread the same way that I can sit in a restaurant, high end restaurant and power where I taught CDOT and eat at $60 a steak with the CEO. I'm able to do both, but I'm able to do both because I had to teach myself that what's okay to one, something big. Speaker 2: (27:32) It was okay that to want to have that $1,000 suits because sometimes we feel that that's unreachable. That's not true. It's very reasonable. If you work hard. Speaker 1 : I love it. Let's go ahead and jump into our lightning round here. So Python or R Speaker 2: Both in the same way that I would say English showed a Spanish. Which one is better for both? Speaker 1 Favorite classification algorithm. Speaker 2 I actually have been thinking about that one for a little bit and I, and to be honest, I don't know all of them. I remember on one session that you were there and I, and I asked you a question and you say, don't be scared to apply even if you're not done with the entire course. You know, I learned the basics and then just started applying until something work. Speaker 1 So what's your favorite question to ask in an interview? Speaker 2: (28:26) The first favorite question that I learned to ask in a narrative, you actually came from Kyle. has this, the very first webinar that he puts out and where he says, you know, to ask the interviewer, what is it that you love about working here? When I heard that one, I went to my wife, I'm like, baby, did you ever ask this question in an interview? Because I never asked that question. My wife was like, that's a good question. I actually knew that the more we thought about it, the more more questions came out to me. You know, like, Oh, what kind of problems do you guys solve as a team? More kind of necessities. You have all this other set of questions that are right around mine, but it was caused question that put the root of my head cause before I didn't use to ask. Speaker 1 Yeah man. All it takes is C little water and then the illumination of your own intelligence. Right. And he just ideas to start coming to manage. So what's the weirdest question that you've been asked in an interview? Speaker 2: (29:13) Not long ago somebody asked me, what's your goal for your personal life in the next year? And I say taking my daughter to a father�s daughter status. Then somebody also asked me, what's the hardest thing you ever had to supersede life? And like I told you before, it was my mother's day. Well, my mom passed. I thought I was done. I thought I was going into the depression. Thank God that my daughter was born three months later. Now that I was thinking about it for your interview, you know, my daughter routes back all the way to the professor of the university of Chicago. And I'll tell you how, because that question assumed that my knowledge was a polynomial degree or even per se. I realize that my life at the moment, my daughter was born, I became my knowledge began polynomial or odd polynomial because my daughter was my inflection point. Speaker 2: (30:15) Wow. The moment she was born, I didn't care how tired I was. I didn't care. You know? I remember telling my wife when I was done with my PhD, say I'm done. I don't need to learn anymore. You know? I crossed that browse where I proved myself, but then when my kid was born, that's when I got more into programming. That's when I got more into reading more books into studying more. She was my inflection point. I was already throwing the towel but wanting to give her a better life. The life I never had has been my my drive in the last couple of years. Speaker 1 I love that analogy. Covered a lot here man. I want to know if there's, there's anything that I missed that you want us to know about Speaker 2: First and foremost. Thank you. Thank you. Thank the DSD J team because you guys are awesome. Speaker 2: (31:02) I mean week, I can go to a slagging, throw a couple of questions and like I say, you're your peer for San Francisco and her name escapes me. Can remember, um, Mickey, what? I wanted one, one of the interviews here for the federal home loan bank, they asked me a question the next day I went to office hours with my Kiko and say, Hey, have you heard of this? Awkward on the day. Asked me to say, Hmm, what about this one? And pointed out to a book and I went and research and I happened to go to the next round in interview and I actually told the interviewer, so the algorithm that you asked me before and they're like, you actually looked it up. Oh, it's like I actually, so it helped. Right. You know, I'm pretty sure it impressed them because they gave me the job. The things that you guys do as so amazing, you guys are changing lives and I appreciate that. Hey, thank you so much. Speaker 1: Just for anybody listening, this is not a paid advertisement. I appreciate, I appreciate those kind words. So how can these people connect with you? Speaker 2 : People can just send me an email to detail. Uh, the Telo, T as in Tom, E, L, L. O, Bravo, B. R. a. V. O. M. E. dot com or chairs reach me in LinkedIn. Me and my friend Martin Barbato. B. A. R. B. O. U. R. we want to help people as much as possible. Mark is another great scientist. Uh, he's self taught. He has helped so many people by now We want to pay it forward. Speaker 1: (32:41) Awesome. I love that. Yeah, definitely put that contact information in the show notes. Thank you again, man. Really appreciate you taking time out of your schedule. It's been a privilege and an honor to sit here and speak with you today. So thank you so much for sharing your story with our listeners. Speaker 2 Thank you. [inaudible] Speaker 3: (32:57) [inaudible].