Stephanie Camello was born in Harbor City, California. She attended a Catholic elementary school, before moving on to San Pedro High School, where she took advanced classes and was a member of the varsity tennis team. She started her college education at El Camino College, then transferred to the University of Southern California where she studied at the Marshall School of Business. Through her studies, she earned a paid internship at Initiative, a global media agency. Stephanie excelled in her internship and was offered a full-time position as a data analyst, which she accepted, beginning in January 2014. She has since worked successfully with a wide range of different agencies, and is currently assessing her options for future endeavors. Stephanie Camello currently resides in Los Angeles, California, and her personal website can be found at

Tell us a little about the data analytics industry, and why you chose to take on that role.

Marketing data analytics is, in a nutshell, the art of taking in data points from a wide range of different sources, often in many different formats, and interpreting and organizing that data into easily understandable reports. You take all of these individual data points, and you bring them together in a format that can be understood and then acted upon. 

For example, say you’ve got a client that’s trying to target their ads toward young adults, and they need to understand how well their marketing efforts are working with a given demographic. To do that, we’ll pull data from Google, from Facebook, from Twitter, from TripAdvisor, from anywhere else we’ve got ads. That data will include information on how much was spent, how many ads were seen, how many ads were clicked on, and so on and so forth. We’ll also have information from the client, depending on what they’re doing—how many tickets were sold in a given time period, or how many rooms were rented out, or how many products were purchased. But that data isn’t really useful while it’s all spread out like that, and that’s where the data analysts come in. We take all of that data, in all its different formats, and bring it together, to form insights about what’s happening. For example, the data might show that certain ads were shown more often on Website A than on Website B, but the fewer ads shown on Website B generated more click-throughs than the ads on Website A, because Website B is better targeted toward the desired demographic. A properly trained data analyst will be able to reveal that insight in just a few moments via a nice chart, so clients don’t have to spend potentially hours sifting through the raw data to draw the same conclusion.

I chose this field because, simply, I really enjoy the work. I enjoyed the projects at USC that ultimately got me hired on at Initiative. This field is about working with facts, understanding facts, not opinions or hearsay. Taking the facts, taking the data, and analyzing it to understand what it means, and presenting the facts in an understandable and digestible way. I enjoy the work, and I’ve been told many times over the years that I’ve got a natural talent for it.

What surprised you the most when you started your career, what lessons did you learn?

What surprised me the most, I think, was just how many tools there are, and how scattered the information is. You might go in thinking that there’s some database somewhere with all of the information you need on it, but that’s not really the case. The data comes from all over. You might get an incredibly detailed report from Facebook, and another one from Twitter, and when you’re working for a large client, you might have 50 or 100 different sources of data all totalled, and every source is formatted differently. Facebook might give you numbers of comments, likes, and shares, for example, while Twitter gives you numbers of followers and retweets—that sort of thing. And you’ve got to take these and turn them into some kind of directly comparable metric. I might characterize it as ’engagement’, for example. Any time someone clicks or follows, they’re ‘engaging’ with the content. You take all of this information, all of this data, and the challenge is in distilling it down to a 2 or 3 sentence story for your client.

In learning to deal with all of this data, I not only learned the technical skills (Tableau, SQL, etc), but also how people in the industry, in different disciplines, collaborate and help each other. When I’m pulling the data and I see a huge increase in ticket sales, it helps that I can easily find out from the strategy team that they pumped 10 times their normal budget into advertising this month. Collaborating with the other teams helps me to stay on top of the huge volumes of data I receive daily, and to know quickly where to look when something unusual arises.

What is one piece of advice you would give someone starting in your industry?

My first piece of advice would be, if you can get an internship—especially a paid internship—take advantage of that. You’ll get to learn a lot of things about your place of work and your field in general without as much fear or stress about messing up, or about losing your job because you’re new and you don’t know what’s going on. And while you’re at it, take the time to educate yourself on the tools you’ll be using in your field. For data analysis, these tools have classically included Tableau and SQL, but now people are also using Python and R. It’s more important than ever to learn as many tools and programs as you can.

If you could change anything about your industry what would it be and why?

One thing that I’ve often seen is that people can get themselves way too obsessed with the tiny details. Somebody has to count the pennies, of course, but not everyone needs to freak out every time some metric climbs from 0.1 all the way to 0.11—especially if it’s a metric where the change doesn’t signify much of anything until it hits, let’s say, 0.4. These details do need to be tracked, but they rarely need to be obsessed over the way that they often are. So, my change would be, let us data analysts keep track of the little details, and let us show you how those details do or don’t impact the big picture.

How would your colleagues describe you?

I think they would describe me as a hard worker. I’m pretty easy to get along with, very receptive to feedback, and always open to listening to people. When a client comes back to me with a report I’ve written, and asks for something totally different, I’ll take the feedback and I’ll change it. And when I have a task to do, I do it without delay. I have a reputation for always delivering my work well before the deadline, and I do that because I always want to leave a time buffer for others to look over my work and to provide feedback if necessary. I never want to be the bottleneck, so I’m always checking in with my colleagues, making sure things are getting done on time or even before the deadline.

How do you maintain a solid work life balance?

I do like to maintain a good work life balance, and I think having a dog is quite a good push in that direction. You have to walk a dog. You’ve got to take the dog outside so he can run around, and maybe take him out for a long hike on the weekends or after work. Taking care of a dog forces you to get exercise, which is great for the body, mind, and soul.

Before COVID, I would usually see a movie on the weekends, or just find some other way to get out of the house. As a data analyst, the last thing you want to do on the weekend is keep staring at a computer. It’s important to just go and do something different.

What is one piece of technology that helps you the most in your daily routine?

Excel, definitely. In data analysis, Excel is the key tool, and mastering Excel is incredibly important. But sometimes you have to translate your work into PowerPoint, because that’s the number one tool for strategists. So, a good secondary tool is Tableau, because it can do both things—the analyst can load in the data and create the visuals and the pie charts and things, and the strategy team can go in there and look at what we’ve provided. It’s a good combo. So, it’s definitely Excel if you’re all about the numbers, and Tableau if you’ve got analysts and strategists looking at the same reports.

What has been the hardest obstacle you’ve overcome?

There have been many times where I’ve had to change jobs, or I had to move, because we lost a client or the client moved somewhere else. Every job I’ve had except for maybe one, I’ve had to move. The first time, with Initiative, the company lost one of the clients that funded me, so I had to find something else. They try to move you around within the agency, but sometimes it’s quicker and easier to get something externally. So I moved to another agency, and I liked it there, but then the client moved all of their positions to New York. I chose to stay in California, so I had to find a new place to work. One of my biggest accomplishments actually occurred when my agency lost a huge client. I had wanted to transition to client-side work someday, so I took the chance and reached out to that client. A few weeks later, they reached out to me and hired me on, and that was a good career boost for me.

Who has been a role model to you and why?

My role model, in the beginning, was the guy who hired me for my internship at Initiative. He was a lot like me—we were both a bit introverted, but we liked data, and he was able to explain a lot of the marketing side of things to me. He was a good mentor to me for a couple of years until he left the company to move to Texas. But in that time, he really helped me grow into the job and integrate with the work environment.

What does success look like to you?

When I was starting out, success to me originally involved climbing the ladder quickly and at a young age. And I made that happen, I guess. I started at 21 with that internship, then became an Analyst, then Senior Analyst at 24. I wanted to rise all the way to Director, and I suppose I still do. But my idea of success has shifted a bit over the years. Now, when I think of success, I don’t just see the position I’m in, but rather the community I’ve built up around me; colleagues, friends, and family. People who will look out for me, who will have my back, just as I have theirs. Maintaining those valuable relationships is now a big part of my new definition of being successful.