Douglas Graham
Rice University
Houston (29.7° N, 95.3° W)

featuring Gabrien Clark, Analytics Lead, Nike, Beaverton, OR (45.4° N, 122.8° W)

Gabrien Clark is an analytics lead at Nike, where he and his team work with sales data to find performance trends in the marketplace and communicate their findings back to the company. He graduated from Rice University with a bachelor of science in bioengineering and a bachelor of arts in history. During college, Clark was active in several student groups, including the Rice Student Association and Rice Empower, a science outreach program. Clark joined General Motors as a business intelligence developer after he graduated, and he tackled complex problems in a fast-paced working environment before joining his analytics team at Nike in 2018.

We began our meeting with a conversation about Clark’s path from studying bioengineering at Rice to becoming a data analyst. It started with a junior year technology internship, which opened his eyes to how his bioengineering problem- solving skills could be applied to different fields. Clark subsequently joined General Motors after graduation and was immediately assigned important projects that put his skills to the test. He went on to work at Nike, a company that shared his appreciation for creatively using different software to solve problems in favor of being constrained to any specific tools.

After Clark discussed his road to Nike, he explained how his current team works together to reveal insights about company sales and present their results. They first gather and interpret data from Nike, along with a variety of retailers, and proceed to determine patterns about product sales in the marketplace. But discovering these trends is only one piece of the puzzle: Clark and his teammates must also visualize and effectively explain their findings to the company and its stakeholders. Communicating these important findings can significantly affect Nike’s planning process. On data analytics teams like Clark’s, there is a high demand for data analysts who can confidently use data analysis and visualization software and work effectively in teams. Clark advises that students interested in the field should consider building a portfolio of projects using a variety of programming languages or software that they can show to potential employers in their job search.

An interesting takeaway from our interview was that the problem-solving skills you learn through one college major can be transferred to other fields in surprising ways. For instance, Clark’s experiences on bioengineering teams allowed him to quickly adapt to team-based projects at General Motors. Though his switch in fields demanded that he quickly learn the database query and management language SQL, Clark’s broad problem-solving skill set that he fostered at Rice enabled him to conquer the challenge. His experience showed me that although some career path switches may be more difficult than others, the hard work required in any rigorous course of college study gives students the ability to transfer their skills to a large range of industries.

But perhaps the most important lesson I gleaned from our conversation was that unexpectedly tough situations often lead to unexpected growth in skill. When Clark obtained his first job after college at General Motors, the company was rapidly shifting their team responsibilities in the wake of their 2014 recalls. Because of this, Clark was assigned difficult cost negotiation tasks that were pivotal to multimillion-dollar company operations. With the help of a guiding mentor, Clark applied his engineering discipline to the work and solved complex tasks, honing his data analytics skills along the way. Facing and overcoming such a significant challenge gave Clark the skill set he needed to succeed in his current position at Nike. His daily work includes adapting to unique situations and using new data technology, abilities that he gained through hard work and determination. Clark’s road to Nike demonstrates that with the right mindset, students can transform their career paths and emerge as skilled professionals in innovative industries.

Highlights from the interview:

Everyone’s family, community, and life circumstances create an initial role for them in society. What was expected of you, and did you stick to that path or stray from it?

I guess I was lucky. I’ve never really had specific expectations for where I would end up, career-wise. I was lucky enough to have a family that was very supportive. Super early on, in high school/middle school, I wanted to be a fitness businessperson. After a while, I wanted to go into medicine, and after that, I was kind of lost, didn’t really know. Family support really helped out, and eventually when I started getting on a path to technology and data analytics, everyone was super supportive.

At which point during your educational or professional journey did you begin to envision yourself in data analytics?

I took a tech internship during the summer after my junior year of Rice. That summer was one of the big influences, and during my senior year, I was pretty open-minded about what I could possibly do. Luckily enough, we had some pretty great technology partners come to Rice to do on-campus recruiting. One that really caught my eye, because I studied bioengineering at Rice, was someone from General Motors who was previously a civil engineering master’s from Rice. He talked about his transition from engineering to tech and mentioned how it is essentially all about problem-solving, even with technology. It got me very excited, knowing that I could take my problem-solving knowledge from my engineering education and bring it to just about any other field. Data analytics within technology has tons of complex problems that people were trying to solve, so it felt like a really great fit, where I could take—not necessarily my exact education—but a skill set that I honed [during] my education. I could take that skill set and bring it over to this new career path. That was a really big, important moment for me.

Was there any specific project that you worked on in data analytics where you really felt skills being transferred from the engineering classes you had?

I would say literally my first project in my first job at General Motors. General Motors had some pretty big vehicle safety issues at the time I started. So my analytics team there picked up newly added responsibilities. All the experienced people were placed on the priority for the vehicle’s safety, but all the existing projects that they still had on their plate had to go somewhere. Because of that need, my first project was actually pretty complex. It required information and tools to negotiate parts from our suppliers and to determine what the ultimate cost of a part was, including transportation cost. How much did that cost? What is it costing the company? And helping the manufacturing plants negotiate. It was actually a partnership with the research and development team. It was very difficult, but it was one of those things where you have to say, “Okay, these are the constraints. These are the technology I’m using. This is the current data structure. These are the things I can do with that data structure. Here’s ultimately what a report can look like.” And once getting those constraints down, going through the iterative design process with partners in research and development, testing out different prototypes for designs and basically getting to final product. Then working on any improvements, clearing the bugs and maintaining that product, and eventually ending up at what we see in production. That was, I would say, pretty much from the get-go, transferring those skills, applying those rational design practices I learned in my engineering discipline at Rice, and really iterating and building something really cool that’s useful for business. 

When you were solving all those complicated problems, did you have a particular mentor or person who helped you along the way?

Yes, I had a few. Luckily, my hiring manager helped me get set up. So, when I first started, I had someone who had been there only for a year but had built a really nice orientation for doing things the right way, interacting well between stakeholders and managers in meetings. So he really took me under his wing and really helped me out along the way. One of the other groups of people that I really appreciated was this group of people called the database administrators. They’re people that are basically the godfathers of the data, where we put it and share it. They’re really cool people; they’re all kind of older and super nice. When I started my job, I didn’t know SQL. I didn’t know how to design my queries as well. They did a good job of being very patient and helping explain things, help me learn along the way. It definitely made me a lot stronger than I otherwise would have been within the technology field. I’m very grateful for that because I know a lot of places don’t have those people that are willing to help you out like they helped me out. That’s definitely something that’s an advantage in my career, and a big part of the reason why I got my job at Nike, because I knew a lot more than the typical two- to three-year person in terms of optimization. I was very lucky that I was able to find those groups of people to be another set of mentors for me.

What lead you to your current position at Nike?

I had worked at General Motors IT for two and a half years. I went from level zero, not knowing anything about that field, and not knowing the different skill sets that I would need to be successful when I first started, to the point where not only did I know now, but I was hungry for more. I wanted to use more than what was available to me. I started learning Python, I started learning more advanced SQL, how to build more on the side of open-source things at home. And I was using websites like Codecademy and DataCamp to level up. Then, I was [contacted] by a staffing company, which had a contact with Nike. The team here at Nike was basically the dream. What he was explaining to me was they didn’t believe in using any predefined, set list of tools. They believed in using whatever gets the job done the best way. Not being afraid to explore, which is something that I really, really wanted. On top of that, just from a life-experience standpoint, I’d grown up in Texas, born and raised, went to school there, had my first job, all within Texas. So, I thought, you know, Portland would be a cool place to figure out, get some new life experiences. So, it was very fortunate that the right opportunity found its way to me via LinkedIn. In the technology field, people reach out all the time, but it was kind of one of those things were nothing seemed right until that moment. And it just worked out. I’m very fortunate that the people reaching out had a great opportunity for me.

What does your current position entail on a daily basis?

Well, it varies. A lot of what my team does is work with data from our retailers that Nike works with, as well as our own internal direct data. My team in particular focuses primarily on point of sales data. For example, we’ll look at a Nike shoe, we track it, and say how much has this shoe sold through its inventory across all of these retailers. And we’re able to compare it and know the key performance indicators (KPIs) to give us insight into how exactly we did in terms of planning for that shoe. Also, examine things from an inventory standpoint and look into what we could do to improve, based on what we’re seeing in the trends across our retailers.

How do you work together with people on your team?

We work in two-week sprints, where we have a product manager who determines a set of smaller items that we’ll be working on to improve our product or products. Our team will take these individual tasks and work on it, and complete them, and move them over into to-do or in-progress or done stage. That’s a very simplified version of it. During the workflow, we talk to each other and help each other out. We communicate whenever a new test comes up. We sit together and we estimate how much work we can get done. Over time, these meetings are where we actually do estimation and talking through the tasks. We get to a point where we understand how much work goes into the product creation, what tasks we can share, what tasks are better worked on individually. Whenever we are working together, we just hop over to each other’s desks, bring our computers, have any discussion we need to talk about for the particular work at hand. And then when we pass teams along, we take notes, detailed notes, built off of the things we had been doing in the past. 

What skills would you say you use most commonly in your work?

From a technical, hard-skills standpoint, I would say SQL and Python are very important for me. We do most of our data visualization in Tableau. Also, there’s a tool called Microsoft SQL Server Analysis Services. I know that may not mean much, but we use that quite a bit here and in my previous job to build something that’s called ad hoc reporting. So, a large set of people may have a shared question that could be answered with one set of visualization. Ad hoc tools allow you to basically just play with the data and answer your own questions.

From a soft-skills standpoint, I would say communication is huge. It’s very important that we’re able to talk to each other and discuss issues and be able to quickly resolve them. I would say communication within our team is very important.

Another important thing is something called business acumen. One important thing that I had to learn is that learning SQL, Python, all these other languages, JavaScript, whatever it may be, is extremely important to be able to create your products, but at the same time, the other big half of that is you really have to build up your knowledge of the data that you’re working with. In terms of Nike, that’s like really understanding how Nike conducts its business, what we deem valuable from a metric standpoint in terms of point of sales, or finance, or what we stand for in a total marketplace. So understanding those key metrics, how our business analysts look at them, and how we’re using that to drive our company forward. Understanding the whole company’s supply chain process is extremely important, because when you’re meeting with stakeholders, you’re not meeting with people who are extremely technical, so you’re not going to be talking about the ins and outs of your SQL query. What you’re going to be talking about is logic. That’s the common language. Someone who’s working within the business and making business decisions will have a logic in mind, where we look at this metric like this and this is how we feel like calculating it. To yourself, you have to translate that to a query or a calculation, but when you’re talking to a business stakeholder, you really need to be able to talk at the lowest level, the logic standpoint, and realize why it’s important and how it’s used.

Were there any skills from your college years at Rice that helped you in those conversations?

I think in engineering, one of the important things that we need to do is make things concise and succinct and to the point—and back it up with numbers and tell a very good, clean story. In terms of working with business stakeholders and keeping our communication of our team to the point and effective, I really need to use those skills I learned in college. I think it’s important for any other job as well, but yeah, being able to concisely, succinctly, and very effectively tell your story… 

How are science and technology reshaping the work that you do, and what changes do you foresee in your industry coming up? 

I think probably the biggest one is something that’s been coming for a long time, it’s constantly building, and here it’s all about cloud computing. It’s one of those things where more and more companies are doing a great job helping offload the computational needs of the company. They provide these great services that scale up very nicely and are extremely important. It’ll blow your mind if I were to show you, just from a reporting standpoint, how much stronger we got by moving to a cloud-based computing platform.

I think also what comes along with that is this idea of software as a service is also getting really big, that model where everyone is trying to be like a Netflix or Spotify, where they offer you monthly services or whatever time period. They offer you these services, but you pay a monthly fee. You scale up or down what you pay for, and your services go up and down. I think those two things go hand in hand, and I think that’s something that the field is just generally moving toward.

I think one thing that won’t be changing anytime soon is people being the backbone for data and analytics. I think it is extremely important. That’s the centerpiece of everything for me. That’s one of the most important things that anyone going into this field can learn. SQL and knowing it well, understanding your data structure well, and if you’re using cloud-based computing platforms, really understanding the ways that they actually compute and what ways can you improve the performance of what you’re building. With those platforms, understanding how much it’s costing us and in what ways we can reduce those costs—and, with that, still really great products.

What would you say is the biggest challenge facing your industry?

I would say it’s a nice challenge, but I still think that from a demand-supply standpoint, that the supply still isn’t meeting demand in terms of talented workers who come in and do a good job and help companies get along. I think being able to really get what teams need from a human-resource standpoint is going to be a big challenge. I think that’s one of the nice challenges; it’s not a typical challenge. It’s nice for workers, but it is a real challenge companies to face. One of the bigger problems is when you have some big initiative, then you have to hire for that, then you have these gaps where you have to go through a full process. For a big company like Nike, that could take quite a while, so these can often get sidetracked a bit. I think that’s honestly going to be one of the bigger challenges.

What advice would you give to a student interested in your field?

If you want to go into data and analytics, learning SQL, building products on your own, or building projects with a team, and building a portfolio that you can walk through and speak through and give details on how you contributed to building that project out. I think that’s hugely important because, ultimately, at the end of the day, someone who’s hiring you, the thing that they want to know is that you’re going to be able to take the job, and do a good job, and very effectively do everything that you say that you can do on your resume, and also things that they are looking for that you don’t know. Be able to pick up on [new things], be willing to learn, and educate yourself. And I think by building up your own data analytics-focused project, as well as building up that portfolio, would be a huge helping hand for getting hired. I think that’s one of the things that every hiring manager will have to see, a portfolio and a project that you’ve done.

Interview excerpts have been lightly edited for clarity and readability and approved by the interviewee.