Amin, ADP’s Chief Data Officer, explores the transformative power of AI and Data in human capital management. Discover how these technologies are making work easier, smarter, and more human while fostering a culture of care. Dive into the innovative AI applications at ADP, including the ADP Assist feature, and learn how they streamline processes, provide proactive insights, and personalize employee experiences. Amin also highlights the importance of responsible AI practices and the technical foundations that make these advancements possible.
Kate:[00:00:04] Hi everyone and welcome to Life at ADP the podcast. Today is an extra special episode because we, well, I should say myself, Ingrid is on a top secret mission right now, but I'm joined by Amin Venjara, who is our Chief Data officer here at ADP. To have a mean be able to sit down with me today is a true honor, and I'm so excited for each of you to get to meet Amin as well. Amin, welcome to the podcast.
Amin:[00:00:34] Thank you for having me. Glad to be here.
Kate:[00:00:35] Awesome. So I know you, but our listeners may not know you. Do you mind sharing your journey about, you know, when you came to ADP, why you came to ADP and a little bit about your career journey here?
Amin:[00:00:49] Sure. Happy to do that. So the way I got to know ADP is the way I think many people get to know ADP is that I was paid by ADP. In prior companies and actually there was an ADP office around the corner from, from where I live. And so I, I'd see it. And so I have some friends that that work in the payroll industry. And I remember getting an outreach from ADP and I actually sent that, that outreach to one of my friends, you know, who works in the industry. And I said, you know, this might be interesting for you. You know, why don't you take a look at it? And he's based in the Midwest. So he said, no, you know, I'm not interested. Why don't why don't you? Maybe you should give it a try. Great industry. Okay, great. Had a conversation with, uh, with the folks here. And, you know, I just I was really, um, impressed by the way the leadership here thought about, differentiation, disruption, what's happening in the industry. And it's difficult for a company that has been as successful as ADP has been. If you if you look at there's a there's a metric financial metric called TSR total shareholder return. ADP is a phenomenal you know, has just phenomenal, uh, placement in terms of how it's performed, and like on that financial metric. And so as I, I had known that just just from my own kind of, um, interest in markets and things like that, but then I wasn't sure what was happening inside the company. So as I got to meet some of the leaders, I was like, wow, this is a company that's performed incredibly well, that has leaders that have this very thoughtful approach.
Amin:[00:02:27] And there seems to be these new vectors of growth that sit at the company and specifically ADP's been, you know, phenomenal with payroll and then the broader human capital management. Think about HR, recruiting, benefits, time, retirement, the kind of the higher to inspire to retire life cycle. But then there's these vectors of where where the future growth can come from. And one of those that I saw at that time was data, right? I was like, wow, this company is sitting on, nearly 20% of the US working population, right over 25 million people paid each month, you know, incredibly powerful data, a sticky relationship. And right now, at that time, I joined ADP about nine years back. The, the, the way that that the data was being harnessed was still, you know, early. And so I was like, wow, that could be something really powerful. So for all those reasons, I entered within our enterprise segment, um, and kind of compliance, what we call compliance solutions, where we serve kind of some of the largest employers to ensure they have the right compliance around tax and payments, you know, the ACA provisions and tax credits and others. And so I started there, but I always had my eye on the data, as kind of something to be powerful. And then in my next role, literally within about two and a half years or so, I was able to find myself in a role leading the product management organization for our our data platform, what we call Data Cloud. So that was kind of how I got started.
Kate:[00:04:09] It's absolutely amazing. And thank you for sharing. So a couple of things that I picked up on is it's not lost on me that you are our Chief Data officer, and the proof points in regards to why you joined ADP, and even we're interested in exploring ADP. Um, was very data driven. So that's that's not lost on me. But I also, um, you know, something that we hear from so many candidates and people who join the organization is that one of the main reasons they join outside of the amazing leadership is the amount of data that we have. It's bar none. And because of so much data, there are complex challenges to solve and evolve towards the future of human capital management, which you, you know, shared. So thank you so much.
Amin:[00:05:06] And maybe just building on that, you know, when I think about and I, and I have this discussion with people internally at ADP, but also as I think, you know, as I have conversations about how people can grow their careers and as I was approaching ADP, one of the best pieces of advice I got early in my career, actually, was it was during my college days. A professor told me, choose your professor, not the course. And I thought about that a lot because oftentimes people are, you know, trying to go after maybe like, what's the latest like hot topic that that you want to go after or work in a specific industry or on a specific area or these kinds of things. And that that wisdom that my professor shared with me, he said, choose your professor, not the course. Meaning it's the people that you're surrounded with that will make the biggest difference in how you experience, a course, a work, um, anything. And by really understanding that even if the topic area might be what's something that you've known before or maybe is super in the news, if the people are super, you know, just really engaging, they bring out the best in you, doesn't matter what the topic is, it allows you to be your best. And that is what is so inspiring. Um, and just makes you want to get up every day and go do it, whatever that is. And so that's something I've kind of built as a, as a guiding principle for me and found it to be helpful. And I think, um, something I try to pass along as, as I talk to other people about their careers too.
Kate:[00:06:45] So I think, Amin, I think that right now people have just leveraged that as their forward thinking guiding principle. So thank you for sharing that. Um, passing it forward, I love it. So let's let's talk a little bit, a lot about GenAI at ADP. I think people would be extremely surprised with the amount of work and focus that's happening at ADP within the GenAI arena, So you know, what can you share with us about that?
Amin:[00:07:22] So there's a lot of things happening here within the human capital management industry and ADP in particular. But let's start by actually taking a step back, because I think all of us have experienced in some way or another, the impact that AI has had on our lives. And if you zoom out, AI has been around for quite some time. We can go back to the 1950s and see the the papers that were written on neural networks that kind of originated a lot of this. Um, and there were actually commercial applications that were happening. Even one that's really interesting is, um, the, the algorithms used to they're called Adaline, and Madaline came out of Stanford, I believe, um, were used to, to limit echoing on, on um, landline telephone landlines. And so they're able to kind of detect, uh, echoing signals and then minimize those so that you could actually have a better phone conversation. So just to make the point that AI has been in production at scale, having commercial applications for some time, um, now, obviously we had the AI winter and came out of that, and then we've seen AI, you know, you've seen it in a lot of different ways. You've seen it, you know, uh, playing chess, you know, against the Grandmaster on Jeopardy, but also within your favorite streaming services and, you know, around you as you're using, you know, uh, maps, functionality and all kinds of stuff in our daily, you know, consumer and technology life. When we think about what's happening specifically in the world of HR, the way we think about what products can do to to help work life be better, we think about three broad principles, right? How do we make, uh, your work easy? How do we make it smart? How do we make it human? And that's, like, fundamental to how we think about our overall product strategy and what we're trying to do.
Amin:[00:09:17] Because if you think about somebody just coming to work, right, what we provide is a way to enrich that company and that workers work experience. And there's some basic things you want to get done when you're onboarding. You want to just, you know, sign up for your benefits, make certain elections for when you want to get paid, how you want to get paid, adopt some policies. And you want it to be easy because you want to be done with it and you want to get on with your work. And there's many things like that. Maybe you just had a kid, and you want to be able to follow that transaction and add them to your benefits. Great. You just want it to be easy. There's other things where you want it to be smart, right? You should know me. Like give me proactive insights. If I'm leading a team and I have a I lead a region and there's a number of stores that I support, I don't have to go look up every single store, tell me what I should be looking at, right. You know, push to me the the anomalies or the the things that should catch my attention. So those insights are what I focus on, and then I can be more effective in my work.
Amin:[00:10:19] Right. Turnover is jumping over times you know an issue. So I can then go speak with that specific store. But finally, like when you think about human, we are in the business of human capital management, right. And and there's this, this, this thing of data in our world, every single data point is a human being sitting behind any data point is a person, their particular life circumstance. There's the specifics of what what makes them tick, what makes them love their work, loathe their work, what what helps them to feel their best and feel like their strengths are being leveraged. All of those things. And we know this in our personal lives. It's everybody is a is a unique combination of factors. And so the data that we're talking about here isn't coming from, you know, machines or representing machines or signal processing or whatever. It's about how do you you maximize the strengths of a human so that that collective of humans can then, you know, fulfill the purpose that they have, whatever that business is, it's, you know, manufacturing some product, producing some software, providing services, running a hotel, running a restaurant, you know, serving in a hospital, whatever those are. That's what we aim to do. And if that's our goal, if that's what we're trying to accomplish, how can I help us do that better? And that's the fundamental question, because too often we talk about AI and AI. You know, it's kind of the latest buzzword, but it's it's just a new capability to solve the existing problems we've always had, right. And maybe problems is too strong of a word.
Amin:[00:12:07] There's things that there's things that we want to enable to work better. We want work to be easier, smarter, more human. How can AI help us do that? And when I get asked this question and talk to CHROs, you know, heads of HR or heads of payroll, heads of, you know, um, uh, that are leading recruiting in different organizations. The way I like to think about this is AI helps us create a culture of care in an organization. What do I mean by that? I mean that AI helps helps companies to harness the power of data to create a culture of care at the speed and scale of business. And what I let me kind of give you an example that that kind of maybe make this more practical. So my mother in law lives in Chicago and, um, every, every few months she'll come visit us. And when she comes to visit us, she brings two bags. She brings small kind of little duffel bag and a big, heavy suitcase. In the duffel bag, there's kind of some personal items, some things that she has for when she stays with us. And. And then this big, heavy suitcase. And when she arrives, um, my kids and I, like, we all kind of come up and greet her, and my kids get super excited seeing, um, their grandma and they, they give her a hug, and then they make their way to the big heavy suitcase inside. That is a you know what she's kind of prepared coming to our house. A whole array of home cooked food, right, a whole suitcase full.
Kate:[00:13:42] Wow
Amin:[00:13:44] Right, like full of just all kinds of stuff. You can just imagine, like, all the different tupperware's and everything. Like, I always I always tell people like, I don't understand, like there must be some special level of of airport security for grandmas, like, you know, PreCheck Global, you know, global, uh, security and then grandma, because what she's able to pass through is just amazing. And so, um, she, you know, she does all that stuff and is able to cook and prepare and bake and everything. But here's the thing. She never once asks us what we want. She just knows. And she hits the mark all the time, right? Like, everybody loves what she cooks, right? And it's never it's not always the same stuff, right? She's making. Maybe she'll make some more dinner stuff and some more sweets or whatever, and she'll choose those things and she'll just bring it. And she she packs all of it. And that's that kind of like, special, like grandma sense, you know, that. At least, you know, I see, you know, through through her. But you think about this. Anybody in their life will know that person who just knows them, right. They get there's somebody who just gets you right. Maybe it's your a parent, it's a friend, it's a spouse or whoever that is.
Amin:[00:15:01] That person just gets you. Why can they do that? Why can they just know how to work with you? They know what you're feeling even before you know how to express it. They know what you're trying to say, even if you don't know how to say it. There's someone that you can sit in silence with and still have a conversation. Why is it that that person can have that kind of relationship with you? It's because that their algorithm of care has been trained on this data set. That is you, right? They see all these different signals that come from so many repeated interactions of like how you operate when you're happy, how you operate when you sad, you know, when when you're going out, when you were younger, as you got older and they've seen this pattern of interactions and signals that you don't even know you're emitting, they pick up on all of that, and that's why they're able to be such a good friend or spouse or parent or, you know, a relative to you because they've honed that algorithm of care to really tailor it to you. So this is what I mean by creating a culture of care that is that capability.
Amin:[00:16:03] When you think about HR leaders at companies, all of this data is flowing through their HR systems, about every single worker sitting in their organization when they were hired, what jobs they're working on, who they report to, when they were paid. Um, you know, when they decide to take time off, you know, benefits that they added when they punched in and punched out and the list goes on. And all of those things are recorded in a human capital management system. So all of those signals are kind of what we would call latent signals that are sitting within the system. The promise of AI is that it can unlock that capability because that's hard for a human, you know, like, again, on a small-scale company, you can have those personal interactions with each individual and know what's going on because the company is small enough. But as it scales, there's there's so many people and so many different life stories that are happening and work stories that are happening. It's hard to keep track. And this is where systems can help provide the data, that's allowing us to then be able to deliver that culture of care that makes HR easy, smart and human. That's what we're trying to achieve.
Kate:[00:17:16] I absolutely adore how you not just framed this, you know, this being the GenAI mission, the easy, smart human into the culture of care. You know, it's it's so relatable. And and thank you for sharing the story about your mother-in-law, because I was nodding my head, um, which I know you saw, but I'm sure many of our listeners were as well. We do have people like that in our lives that just know. But I really love the way that you've taken us from an organization that people probably know from their paycheck or their app, where they now get their paycheck. Um, to really much deeper than that, you know, that culture of care. Um, you know, the, the organization, company people behind it that are looking to build comfort and trust to know what those things are happening in each of the data set, aka human lives. Um, that we are, uh, not only, um, not only that we have access to, but we have a lot of responsibility to, right. Um, so, so thank you. I, I love that.
Amin:[00:18:32] Absolutely, and so, so let's take, uh, some use cases to kind of help make this more practical, when we think about, you know, the value that that AI can provide to organizations and to and specifically with, with ADP strategy, we think about it in three big buckets. The first is how we can reimagine the product, right? And just create a fantastic product that we can deliver to our to, to companies, both the the HR practitioners, the managers, the employees of that of that company and make their work life better. Another pillar of this is how we can create a service experience, like for for how we actually deliver on the questions that people send us, uh, for, for how we can support them and make things easier within our own internal operations. And finally, we have a lot of ways and a lot of solutions that we can offer to companies. How can we grow our, uh, our what we our sales and allow our sales teams to be more effective, more targeted, and be able to engage with customers to things that are relevant to them. Those are kind of the three big areas we think about. Let's take a let's kind of focus on the kind of product, one that the product that we provide to our end customers. I think all of us, when we think about, a work experience, we'd be great if like, wouldn't it be great if we could just kind of ask what we want to an HR system and get the answer back? Or even better, we could do that, but it could also just know me and proactively provide what I need at this moment because it knows what I'm going through, right? It knows that I haven't taken vacation in a long time.
Amin:[00:20:15] It prompts me to say, hey, look, you have this much PTO balance. You know, it would be great if you could. You know, you should think about how to use it. By the way, maybe even here are some offers that that you could take advantage of so that you can you can have some some ways to get discounts and use up that PTO time that's appropriate to you, right? That's the kind of experience that I can bring. So when we think about the value of where we're going to go with the product, we've, we've announced recently the notion of what we call ADP Assist, which is a product capability that we're going to be tying into all of our different platforms that we deliver from the smallest businesses up to to multinationals and internationally that allows HR professionals, employees, executives, and managers to be able to to really drive and have the process automation, the proactive insights and the personalization they need to make their work life better. Let's take some examples to kind of make this real, right. So at a basic level, if I'm running payroll, right, there's a number of steps that I have to do in order to be able to do that as a payroll practitioner.
Amin:[00:21:24] And here's the thing you cannot get payroll wrong, right? This is something that everybody expects like 100% accuracy. Right. And we all depend on this, right. We all depend on this check that we get to show up and to be to be right down to the cent. And so think about what that means for the person in your organization today who's responsible for that or the team that's responsible for that. And there's so many different inputs that go into a payroll. Right. How many hours did somebody work? What's the pay rate that that they have, you know, was there any leave time that, that they had to take in, take into account new hires that joined? When did they start all those kinds of things? And so all that data has to be put in. So then and then you have to think about the taxes that have to be taken out, any benefits or any deductions that are, that are in there and calculate all that, what we call gross to net, right. So what's the gross amount that you're paid. What are all those deductions that come out, and then what is it net out to. And with taking in all those compliance considerations, what's happening, data at the company. There's a lot of data that's being put through, if you have to be right. If you have to be right because each individual's family is depending on you to get that right, you want to make sure that you can.
Amin:[00:22:40] You have the best capability to alert you when you know anomalies are detected or errors are showing up. So as an example, you might have a company one one capability that we're actually piloting with clients today is imagine you have a company that's operating, let's say in, South Carolina. I'm just going to pick that like a state in the U.S. right. So you've got South Carolina, you're operating there. You recently hired people and expanded into North Carolina. Well, guess what? In order to do that, there's tax implications of setting up in a new state. You actually have to have a tax ID that's set there. Now, if as a system I it would be smart if that system would notice that you have people that you hired that work in North Carolina, but you do not have a tax ID, um, in input into the system for North Carolina. And that's going to lead to errors in your in your employment taxes, employer taxes, right. And so it would be great if the system proactively alerted me to that. Let me know that I have to do this process. Maybe I don't know because I'm expanding newly into new state. What do I have to do in order to be able to get that tax ID? And how do I input it into the system to make that happen? That's something now that ADP Assist is is currently doing for our clients, right. Enabling them to think about some of those compliance things they might not know.
Amin:[00:24:02] They have to take advantage that they have to they have to account for and be there proactively and help them complete the whole journey to get that done. Let's take another example. Um, I want to, you know, if I, if I, if I imagine I'm a manager, uh, of like a certain region of stores, right. And so it's really important, like, I imagine I'm, you know, set of restaurants, it's really, really important to run a restaurant, uh, that people come to that that though, that I have workers that are there from the waiters to the front of house staff to the cooks to everybody. And it's really, really important that we have we're staffed up, we're scheduled right, and we can run our operations. Now, I can't be at every store at once. And so it would be great is if, if I start to see some new hire turnover jumping, meaning when people who just joined us and they stay with us for a little bit and then they leave. Um, that to me indicates that, you know, there's an issue with what we're doing in terms of bringing people into the organization or keeping them when we're there, right? Maybe we're not bringing in the right people. Maybe we're not doing enough to keep them there. Something's going on. I would love it if my HR system would proactively tell me that so I can then know, ah, this is something I should be focused on.
Amin:[00:25:16] So that's another thing that we're working on and we have today in ADP Assist. We're piloting this with clients so they can get proactive notifications from their analytics to say, hey, your turnover jumped or your new hire turnover jumped in this specific location. Here's what you should be doing about it. And guess what? When somebody leaves, they're already gone, right? They made that decision. They decided to leave. But there are people at your company that are still there today, so you want to make sure you're doing everything you can to understand how are they feeling, right. What's going on? How do I ensure that we're creating their best process for you to feel engaged, right? To feel like you are having, you know, a valuable experience at work. So we actually have also the ability to deliver surveys. So the ADP Assist is actually now embedding the survey process. So you can actually deliver up a survey uh, to the to the specific people that are in that location and, and are still there. So you can get a sense of how they're feeling about what's happening. And now you have these data points. Well, I know people have left. I have sentiment of the people that are around. What kinds of conversations and what do we need to do to put in place to be able to take action and ensure that we're we're helping that that restaurant to be able to grow and make our people feel engaged and productive at work.
Kate:[00:26:33] And you know something about that, too. And you, when you use an example such as the restaurant, you know, the people that leave, although they've left employment, you also want them to consider still being a client. So you still want them to think fondly of where they were working to bring their family or their friends and or to refer people to go to that establishment. So seeking those data points will not only help the attrition, but will also continue to grow revenue numbers. When you think about it, because it's not going to prohibit people from referring people to go back to that establishment.
Amin:[00:27:09] That's right, that's right. It's so critical, right, to make all this happen. And, you know, just another piece of this whole hiring puzzle is kind of salary benchmarking, right? Recently, um, we've actually have kind of we've put a lot of work over the last, you know, call it 7 to 8 years on on a salary benchmarking capability that takes data from that's sitting in the payroll systems. And we're able to think about all these 25 million people that are getting paid. We know precisely what everybody's getting paid. So our ability to be able to compute a salary benchmark, um, gives you kind of accurate data of what somebody makes in a particular job in a particular location at a particular time, right. And we've seen changes of that. I think back to the Covid era. I know it's actually not that long ago, just four years ago. Think about what that was looking like, um, for Covid and all the different changes we saw in the disruptions. Having access to accurate salary benchmarks is so important for employers to make sure they get the right talent at the right price, you know, in the right locations. And to know what's going to be. We actually recently published an article, we had some, um, uh, researchers from Harvard and University of California, Berkeley. Uh, we published it, um, in Harvard Business Review, showing the impact of what salary benchmarks could drive before, uh, you're using kind of AI generated salary benchmarks and what it can be afterwards. And you can see like 2X difference in setting the right salary, reduction of overpays of salary, and just an ability to be able to be more effective in your hiring practices. This is the kind of impact that real data can have to drive value for organizations.
Kate:[00:28:51] Thank you so much for sharing those use cases, they were absolutely, they absolutely resonated with me, you know, but but I'm curious too, if we can just shift to your overall and the team's overall approach to data. So can you share a little bit about that?
Amin:[00:29:06] I think it's important now when you think about from a technical perspective, like what are we doing to make these use cases possible, right. And how do we actually, build the platforms that we can do this at scale. So we think about this in a few different pieces. The first is obviously the underlying data platform. We have put in a lot of work over the last decade-plus to, be able to build the build all of our data flowing into a central, data lake, that that we have housed. We have that data catalog. We have the lineage around it. We have anomaly detection on that data. We have, we have structured data and now we're bringing unstructured data into that platform. So there is a common foundation that everybody can use. And we have developed a permissions around that data. Done all the contracting work. So just all the foundations you need in order to actually be able to do the data and AI work that needs to happen has been, you know, decade long investment, uh, you know, that that has happened across the company. And so from that foundation, which again, covers over 40 million people that we pay across the globe, right. Um, over a million different, uh, companies that we serve. That's a tremendous set of data set to pull from, right. But it's not just the data that comes from those companies,
Amin:[00:30:35] kind of of the specifics there, but also because of our business model where ADP set up. We actually have a very deep service organization. So we interact with our clients in a very deep way. We understand how they're using our systems. We're not just a SaaS company. We are technology and service that's core to our value proposition. So much so that we have a division of our company that actually we which is kind of BPO or business process outsourcing, but we're actually be the HR or payroll arm for companies that want that level of support from us. So the the point being is, especially from a data perspective and technology perspective, the insight we have into how the data is being used and then the conversations from customer chats and transcripts. It's very rich. So now you can combine the structured data that's sitting there about what somebody paid or what somebody is clicking on in the system with the the transcript data and the chat data about how people are talking about what's going on. And GenAI allows us to unlock that, to now be able to power an experience where more of that can be done via that, that kind of chat type of interface, like an assist, the ADP Assist that I talked about that can both serve our customers, our service teams and our sales teams. So that's kind of the data foundation, right? Then we have kind of an AI platform that sits on top of that where we have common AI services, right? That can be leveraged off of that data.
Amin:[00:32:14] So think about things like a summarization service. You have things like a nudging service, anomaly detection, kind of common AI services that can be used across, across teams so that it can accelerate the work that they're doing right, to drive end value for customers. And critical to that is kind of like a human in the loop type of feedback, right. That that's happening. And again, one of the things that I think that our business model allows us to do is because we have that data set, we both have a way of being able to have, you know, expert labelers, so that that we can get the, the data, the test sets to actually be able to validate, the the outputs of the models, but also to be able to then do the fine tuning of the models to be able to ensure we can do fit for purpose in the way that we're delivering value, but also to be able to leverage that data to be able to use things like LM as judge, right, so that you don't have to now start to, um, to start to build out and always rely on kind of a human in the you can have the human in the loop experience, but be able to train the models to be able to actually serve that purpose and accelerate the way that we do that validation process and the, the, the completion of the validation loop with whatever we produce.
Amin:[00:33:38] So you kind of start to think about all of those different capabilities. And then, fundamental to all of this is kind of a responsible AI approach, right? Because it's really, really critical that we we've we establish the right principles, guiding principles of how the data is going to be used, how AI is going to be used, and and have the right processes in place to be able to, to make that part of our culture and, and also the right tooling to do that at scale. So all of those pieces, you know, we've set up a in an internal and external, AI ethics board that reviews all of our cases and use cases that we go through, and provides guidance. We have an internal process that goes through the use cases to ensure that, you know, we're doing this in a compliant, ethical manner, but also to to see synergies between different teams and then the right kinds of tooling to ensure that, um, we can we can monitor how data is flowing, which models it's being used with and for, um, and then and ensure that we have a, an appropriate set of safeguards, um, for, um, safe, private, accurate and secure use of our data in the, in the AI processes.
Kate:[00:34:52] What I appreciate that you've hit upon within the group principles and the approach to data that you know, your overall team takes is you have also, unknowingly, uh, yet probably very strategically have hit upon some of our just overall core values at ADP. So, you know, results-driven is one of them. Integrity is everything, you know, that's a clear indicator of the ethics in which you were just referencing, you know, service driven service excellence. So I really appreciate and respect the work that you and your, your entire team are doing around this effort as well as, you know, the evolution of the products. It's extremely inspiring. I love absolutely hearing, you know, all the work that the team is doing. And I appreciate you sharing that with all of our listeners. Amin, I have no doubt that people are like, okay, so I'm blown away by the work they are doing. How can I join this team? What does it look like? You know, what can I expect? What candidate profile and traits, you know, can we talk a little bit about what you look for, for people to join, you know, the data teams and the GenAI team at ADP?
Amin:[00:36:13] Yeah, absolutely. Um, so look, we you know, as you can tell, there's a lot of work going on. And through that, you know, we're looking for you know, we're looking for talent, you know, for people to help us grow and help us grow in a number of different ways. So really with it within our group, we do four big things, you know, we have the central data platform, the central AI platform, the data and AI governance and the commercialization capabilities, where we kind of run the business of how we commercialize data. And that's that scope has a lot of different talents that we need. We obviously need data engineers who are going to be able to help us, um, you know, build the right pipelines, ensure we have the right monitoring, ensure we have the right capabilities within the overall data platform. Um, so that's that that's fundamental. And we have a lot of open roles there. On the AI side, you know, from data scientists, you know, for helping us to be able to do the actual modeling, working, uh, both in the kind of traditional AI and AI space, to AI architects, to machine learning engineers that can actually help us to productionalize and ensure that we can deliver the capabilities we have at scale. So all of those are important roles that we need to be able to grow out. But also within data and AI and governance, we need people who are experts in security and privacy and be able to know how to run governance processes to ensure we have the ethical and responsible use of our data, right.
Amin:[00:37:39] And so we have a team that's that's developing and growing there. And then finally, like a set of you think about growing the commercial side of of actually developing the products, right. So we have, you know, actually, you know, the full stack of applications, you know, for we actually then have from product management application developers, you know, who are both UI and back end, to be able to have UX designers to be able to come in and help us build our analytics product, build some of our API products, help us to be able to develop and grow and folks that can help us, you know, think about the strategy and market approach to how we want to get there. So there's a ton of these, you know, opportunities that we have. Data is a growing space. I'd encourage any of the listeners here to to visit tech.adp.com, you know, look at things around data solutions and all the kinds of different roles that we have posted from any of those categories. And really what we're looking for is folks that are customer obsessed, they love to move it like a startup type speed, because we are kind of an innovating group within a larger organization. We have the resources and we have the kind of strategic alignment to be able to move. And we're looking for people who are excited about creating an impact and making a difference and really thinking about outcomes, not activity to drive customer value. So if that sounds exciting to you, we'd love to to to have that conversation.
Kate:[00:39:00] Thank you so much, Amin. I have no doubt that within the next few weeks, you may see a little bit of a spike happening with the open roles that you have. But, we so appreciate you taking the time to to sit down and speak with me again, Ingrid, she's here in spirit. And, you know, for those of you who are intrigued about a career ADP, specifically a tech career ADP, you know, as Amin said, please visit tech.adp.com, And you know, search for the GenAI, data engineers, data scientists, AI architects, um, you know, security, product development. We have so much to offer here. And it has just been a real treat to sit down with you. So thank you so very much.
Amin:[00:39:48] Thank you so much.