Why I Decided to Study Data Science After 10 Years in Marketing

Photo by Franki Chamaki on Unsplash

How It Started…

When I originally started college, I thought I wanted to be an entrepreneur. I quickly realized, like most people attracted to that lifestyle, there are particular elements that I was enamored with but enduring the sleepless nights of being the single point of failure for an up and coming business seemed far too daunting for my already anxious mind.

The part of the business journey I did find myself most attracted to was marketing. It might have had something to do with the fact that I laid an egg in every significant business class in college besides the marketing ones. Either way, I’ve always felt a calling in providing value to people and I saw marketing as the strongest vehicle to introduce customers to a product or service that would improve their quality of life.

Key Takeaway: Discovering what you don’t want can sometimes be the most important step to discovering what you do want.

I spent 3 years at a non-profit after college, taking on a myriad of roles supporting the organization’s marketing and fundraising efforts. This type of work aligned with my values as a marketer because I truly believed in the organization’s mission and our efforts to improve the quality of life for the people we served. However, around my second year I began to question some of our decisions and it’s here where I learned an incredibly valuable lesson that became the first data science seed planted.

At our organization, we would do these volunteer projects with, [insert any Fortune 500 Company], we’d take photos, and then it would immediately be posted to the company’s social media with an inspiring caption…they may even commit to a monetary donation.

Harmless enough, right? But after every event, I would be left asking myself the same question:

“How would you measure the impact of these one-off projects within the scope of our mission to help underserved communities?”

Well, I wouldn’t necessarily call painting a room in a rec center ‘impact’ outside of the optics. Even if we count the donation, it’s usually a drop in the ocean for a company worth hundreds of millions and it wouldn’t change life for a non-profit of this size.

I started to dig deeper with my inquiries:

“What’s an alternative action for volunteers/companies to do that would be more impactful? Wait, do we need them to make a real impact?”

I would dig deeper and deeper only to realize that as someone marketing an organization that supports residents in OUR community, we didn’t have a tight enough grasp on the actual issues that affected OUR community. Sure we could provide you with one-off anecdotes, we could even throw some vague stats your way, but concrete, empirical, non-bias, well thought out data on the issues impacting our clients? That was nowhere to be found.

This shattered my world because after that revelation, you can’t go back to regularly scheduled programming. Everything is now in question — conversations about solutions became more difficult because getting a consensus on the problem was almost impossible without the right data. Feeling uninspired by that revelation, I decided to move on from non-profit and got involved in the startup world.

Key Takeaway: There is no substitute for understanding the real problem that needs solving. This could take many forms depending on the business but there is a significant cost to pay for misaligning your resources with the actual problem.

In my search for a mission driven startup, it was important to me to know that my work and impact would be measurable and that there would be an emphasis on solving a problem. A few years later, after working with a couple of growing companies, I decided to join the marketing team at Flatiron School. This is where I was introduced to the world of Data Science.


I took a C++ class in college and my final exam was on paper. Paper. Not a computer that you actually use to write code with. We’re talking about paper. Not a computer. Paper. Paper! (Shoutout to you if you caught the Allen Iverson “Practice” reference. Needless to say, I didn’t get much out of that class.)

In case you didn’t get the reference, please enjoy this video :-).

As I began to learn data science for my role at Flatiron School, I realized that it’s what I had been searching for since my epiphany — a way to empirically identify problems beyond the surface and decide on the best course of action to solve it. I saw first hand how a person with some work experience and countless hours on Youtube could join a community of learners and in a few months produce insightful projects geared towards solving real-world problems. It instantly took me back to my time in non-profit and how this science could be used to help solve some of society’s most complex and nuanced issues.

About a year into my work at Flatiron School I knew I wanted to work in data science, but specifically in the data for good space. Once I made that decision, I decided to join Flatiron School’s program to arm myself with the skills necessary to become a data scientist.

Key Takeaway: I was incredibly nervous to commit to learning this new field. In times of this level of uncertainty, I remember what the late, great Dr. Maya Angelou once said — “Courage is the most important of the virtues, because without it, no other virtue can be practiced consistently.”

How it’s going…

I started by learning the basic application of data for good and learning about organizations like DataKind and Data 4 Black Lives to name a few. I attended conferences, I watched hours of Youtube for data science novices, and I even took a couple (Free!) warm up courses on my own time. Ultimately, I became a Flatiron School student and I’m currently working through the course!

Furthermore, Flatiron School has decided to pivot to a more discipline focused approach and I’ve recently transitioned to the role of Marketing Program Manager of Data Science. It’s now my job to help people like myself who aren’t satisfied by optics and are driven by honest, measurable impact, pursue a career in data science.




Currently a Marketing Program Manager for Data Science at Flatiron School. Also, a Data Science Student at Flatiron School.

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Jelani Thomas

Jelani Thomas

Currently a Marketing Program Manager for Data Science at Flatiron School. Also, a Data Science Student at Flatiron School.

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