so bit of a long story I've had quite and unexpected journey Thio get to where I am at IBM Prior to joining IBM and then a day of science boot camp, I was a math teacher for four years, had taught pre algebra at middle school and then also worked in oil and gas for a year for actually went to refineries and executed whatever chemicals needed to be used to clean during turnaround time. And then, prior to that, I worked for Fox Sports, were helped with some programming, and I got my degree and kinesiology. So you will say it's been kind of a journey. So where I am now, math has always been a common theme, just showing up in different places in different avenues. And so you could. I like to say that math now is, you know, my love and my passion. Andi just Yeah, it's been a common thing

So I at IBM We actually, And we just made, uh, not I should say we but my bosses higher up there was a bit of a reorg going on, but in terms of what I do as a day scientists, it's still consistent. I'm a bit of a data science consultant. So while the responsibilities and decisions I have once a company comes in, buys IBM product were post sales. So we actually implement or develop M v p minimum valuable product as to what the company wants to use. So, for example, last year they said, Hey, we want to improve fill rate for job placement. So one of my responsibilities came down to All right, I gotta build something, build an algorithm toe, ensure that that would happen. S oh, that's just a little preview. Some of the other responsibilities comes down to also educating clients. On what? How not what, but how to use the product. Like, how is this going to be integrated? Where do we see fit? And hopefully, depending upon what we see, where the process is, we go. Hey, you know what? This right now we're working on this. This is only gonna boost what we can do for you all and hope that it all works out. So it terms of the top three priorities. It comes down to just educating and just bringing value to the customer, whatever that may be. And then hopefully really educating them on how IBM can help them and only boost their brand and their footprint. Uh, it's it's a little difficult to say top three because there's so much that goes on within that. So I'm trying to think about how I'm going to break that all down. So that's That's the biggest and largest one from there goes down to education. This world, we're always talking about skills, skills, skills. What do you bring? So I look at my background, I go. Okay, What skills can I bring? Well, I was a teacher for years, so I explain ability, especially nowadays where you hear a times people talk about like, I don't know if a I machine learning their little they want, uh, wanna be a little hands off. Don't want that part of the organization. So, um, I doing a good job of educating them on how a set algorithm works. How it is removing bias, how it's handling the data that's been collected, and then the third kind of priority pain point, I'd say is, How am I? And this is a personal one. But just how my bringing value to the organization as a whole, Um, I doing my job and my executing what I'm saying I'm doing and my hitting the focus is focused, not focuses, but kind of the goals that one I've set out forward, that IBM is set out for me and that IBM just set out for a company and then Thio answer kind of the next question. Like what? Strategies or effective dealing with the challenges? E think this is just gonna tie in tow the personal life lesson, which is B'more educated, and Maura, wear that who you're talking Thio. So that way, when you go into an engagement, when you go into any situation, you yourself I know that I have all the information and some mawr. So that way, when the question comes up, a concern comes up. I know I can answer and I could take care of it right then and there

in terms of software program, anything that IBM currently has in production. I use not not going to say every day because every client is different. And so, whereas one client may want Watson assistant with Watson's discovery, another client may be interested and IBM security So it really comes down. Thio. Alright, do I first understand all kind of software that's being offered? And then I'm able to speak to that, uh, in terms of more of, ah programmatic ways. We IBM offers cloud pack for data so you can do everything from coding and python or are Paice Bar so on so forth? So that's kind of the main software that I would use and then language Python. That's the number one I at my boot camp I learned Python are and sequel with and but I don't haven't used are yet Python. It's the dominant language in the industry right now. It's the one I use the most and the one I found. When I speak to certain exacts of a client, they understand it a little bit easier, and it's easier to communicate in and in regards to models or algorithms anything underneath the sun. It could go from a I'm thinking, when your regression very basic y equals MX plus B all the way to Gan Neural network. It really there really isn't anything regarding those two that isn't not used. I've spoken with co workers who they used a neural network on a project, and then the next one they'll use multiple linear regression. I've used random forest classifier. I've used logistic regression really doesn't. There is no stop. It's mainly how educated M I with those algorithms and models to be able to speak to their application and where they can work and where they can apply.