KIMBERLY NGUYEN – CAREER JOURNEY PODCAST AUDIO TRANSCRIPT Kimberly Nguyen [00:00:00] And it was not why they think, well, this is so hard and it's so until I took AP statistics in senior year of high useless, why am I learning this? And it was not school that I realized how much I actually do until I took AP statistics in senior year of high enjoy math when you can apply math to real school that I realized how much I actually do life. enjoy math when you can apply math to real life statistics was the first time, I found math to Joyce Kline [00:00:15] Hello, everybody, I'm actually be useful. We were looking at a placebo Joyce Kline. I'm a managing director within project where half of the subjects got a new Accenture’s Applied Intelligence Practice, and medication, and the other half did not get the I'm going to be the host today for our AI medication. And I realized that you could use Leaders podcast. And I'm excited to have join math to come to definitive conclusions about with me today, Kimberly Nguyen. Kimberly is a whether or not the medicine worked. So, if it consultant within Accenture’s Applied worked on 50 percent of the people or 60 percent Intelligence Practice, and we're going to learn of the people, how can you say the medicine is today about Kimberly's exciting journey that working or not? Well, there's statistical theories brought her here to Accenture. So, Kimberly, that you can apply to come up with that I'm so excited that you're spending time with me conclusion. So, I thought that was really cool and today to share your experiences. really interesting, and that's why I decided to pursue statistics in college. Kimberly Nguyen [00:00:47] Thank you so much for having me. Joyce Kline [00:02:21] Perfect. Wow, what a journey, in terms of your experiences. What do Joyce Kline [00:00:48] Great. Well, in an you think that society in general can do to get kids effort, Kimberly, to just get started, let's take you more interested in math at a younger age? back to when you were in school. Did you like math? Kimberly Nguyen [00:02:34] Yeah, I think it would be better to teach statistics before any Kimberly Nguyen [00:00:58] I absolutely other type of math. I don't know necessarily how hated math. I remember specifically one test in you do that because obviously you need to know seventh grade, and I remember sitting at the a little bit of basic math before you can really learn desk taking this test, it's pre-algebra where we statistics. But there's probably games that you can had to solve for X. So, there is equations on play with cards or picking balls out of a bag or each side, and we had to isolate X and solve for something, or marbles, to help them understand X. And for some reason, 12 year old me, my why statistics is a really good math to learn. And mind just went completely blank. And that was then they will know that, OK, you also need to the first time I'd ever gotten an F on any exam. learn basic math in order to be good at statistics And I remember coming home with the paper and hopefully that would motivate them more to and crying at the dinner table. And from then be interested in math. on, I hated math. And I find that most kids tend to say they don't like math or that they're not Joyce Kline [00:03:02] Those are some great good at math. And then when you ask them ideas. I think anything that we can do to encourage students to be interested in STEM, stuff and making an impression on the recruiter, we just really need to do it. And your ideas on, that I was able to get my job at Accenture. So you know, elevating the role of statistics is really yeah, the career fairs really helped me get to good. You graduated with a bachelors and a where I am today. graduate degree in statistics. What was your experience after graduation in terms of finding a Joyce Kline [00:05:34] That's pretty amazing job? how you navigated through everything and just, you know, thinking back to, you know, from Kimberly Nguyen [00:03:27] Yeah, my graduation to how do you find your first job, to experience was very interesting. It was also LinkedIn, to career fairs, and now you're finally very, very difficult. I didn't get a job until two at Accenture and you've been with us for a little years after I graduated from college. So, initially bit. So maybe you could share a little bit about I thought that I would just become a data what it's been for you since joining Accenture analyst and just do some basic descriptive and talk a little bit about your roles. statistics and build some visualizations and graphs. I never thought I'd be modeling and Kimberly Nguyen [00:05:58] Yep, so I joined coding, but I was a first generation college initially in the consulting development program. I student, which means that I was the first person wasn't aligned to any specific industry or any in my family to graduate from college. And so specific department Accenture, but I knew that I everyone in my family worked blue collar jobs, wanted to be a part of applied intelligence I'm the first one to work any white collar type of because that's where all the cool data science job. My mom was very excited whenever she stuff happens. So, while I was in the consulting sees me with a new business card every time I development program, I really made sure that get promoted. But because of that, I did not no matter what role I was on that I set my brand know really how to get a job. I was kind of so that people knew that I was the data science taught, OK, you get good grades, and the more girl. I was a data science person. I love data. I degrees you get the more eligible you are to get want to build models. I want to code. So, that a job. And that as soon as you graduate, you was very important to me. And the thing I love get a job right away. I realized that that was not, about working at Accenture is that I've worked in in fact, the truth. And I did not realize that if you so many different types of industries and I've apply to jobs online, your resume basically goes done so many different, I've had so many into a black hole and no one ever sees it again. different roles across data science. So, for my So, I realize that being a data analyst also was first role, I was a PMO lead for a retail client and no longer a viable career because everyone that had nothing to do with data science at all. was becoming a data scientist. So, I thought But I learned a lot of good organizational skills. I maybe I would pivot to becoming an actuary learned how to make decks. So it was a very and that wasn't working out either. So, I realized good first project for me. Then I was on an that networking was a really important part of internal role, which means I was doing work for finding a job. So, for the two years where I didn't Accenture, where I was just a data analyst and have, I say I'm unemployed, but for two years I we were using just some descriptive statistics was working minimum wage jobs and then that I created in excel in order to help Accenture during my lunch breaks I would go to all the figure out where all the computers Accenture career fairs at my college I had just graduated that had not yet been upgraded to Windows 10 from. I would also, I made a LinkedIn and I were sitting, in what regions, on what projects, reached out to completely random people on and how we can tackle them and drive the LinkedIn that had jobs and worked at number of computers that had not yet been companies I was interested in, and I would go upgraded down to zero. So, that was just a data get coffee with those people and ask them for analyst project. Then I moved on to a career advice. I actually applied to Accenture government role where I was a data the first year that I was looking for a job and got visualization developer where I had no idea rejected. It wasn't until I came back for a career about Power BI or Tableau. And just by learning fair for the second year, I was applying jobs on the job, I was able to become a Power BI where I had learned about networking, all that sneed. We were able to help build really advanced dashboards in Power BI that pushed really valuable skill to have and will really help the limits of the tool. And then we were able to you get a job.