For the longest, data science was one of those careers I respected from afar; mostly because my big brother’s been doing it forever, and he makes it look like something out of a spy movie. He’s the go-to tech genius in the family, but with our age gap (eleven years, to be exact), I mostly just cheered him on without asking too many questions. It always seemed… complicated. However, he has played a major role in my career success.
A few weeks ago, a Black Orlando Tech event focused on data science popped up on my LinkedIn feed. I figured, why not slide through and finally find out what this data life is all about? Enter Natesha.
Ten minutes into her presentation, I was completely dialed in. She had a calm confidence, explained everything like a true expert, and made all that number-crunching make sense without dumbing it down, which is definitely a skill.
I knew I had to meet her and share her story. So… here it is.
Let’s start with the obvious—what does a typical workday look like for you as a data scientist? IRL.
As the new founder of a startup tech analytics company called Data Swale and a Computational Analytics graduate student at Georgia Tech, my days are a hodgepodge of activities. I start my day with a priority list of goals I’d like to get done.
Simple tasks like business documentation or organizational to-dos that can be done in 30 minutes or less, I knock out first. They are quick achievements and provide a sense of accomplishment early on. I then have one or 2 challenging items, such as data projects or homework, I like to work on for 4-8 hours.
During my mental breaks, I prepare for coffee chats. Network virtually. Sign up for events. Eat. Garden.
Did you always know you wanted to work in data science, or did you kind of stumble into it? And just to settle the internet debate; is data science a good career in your opinion?
Data Science was more of a recent discovery for me. Growing up I’ve always been a bit of a gold-star student with a keen interest and talent in math and business. My undergraduate degree in Finance from University Central Florida pulled me into banking/investments for about 3.5 years after college.
During that time, I knew going forward I wanted to be in more mathematical and technologically intensive roles to challenge myself and satisfy my passion to build and make scalable impact.
TLDR; While working in banking, I went through several phases of wanting to get a PhD in Mathematics and Economics. I was taking a lot of higher-level college math and coding courses as grad school prerequisites. I also took data analytics/science courses for fun, and I began adding data science to my grad school radar. Soon after, I realized that data science was for me!
Data Science is an awesome field! Of course, I’m “biased”. But I’d also say, any career where you are passionate and driven to constantly develop yourself is the journey you should be on.
What tools, platforms, or languages are in your daily rotation?
I’m a fairly simple person when it comes to my everyday tools. Python, Excel, SQL, and R are my go-tos for anything data. For operations, I’m usually in Calendly, Canva, and PowerPoint.
Also, a little ChatGPT here and there. For the most part, I find that hyper-specialized tools end-up costing me too much time to learn or aren’t worth the buck.
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For someone reading this who’s still in school or thinking about going back, can you major in data science? Or do you think it’s more about experience and upskilling than the degree title?
For someone who is still in school or thinking about returning, yes you can major in data science. Data Science is an interdisciplinary field involving math, computer science, and business domain knowledge. Data Science is a fairly new major/program in colleges. Be sure to look for universities that have quality math and computer science programs.
Overall, if you are not currently in a technically adjacent career such as Mathematics, Statistics, Computer Science, or in a highly quantitative advanced Data Analyst role I wouldn’t recommend trying to become a data scientist without formal education.
As someone who is currently in grad school for data science, has always been a lifelong learner, and has taken several data science/analytics and coding courses online prior to grad school, the self-taught path is not a great route to take from a non-technically adjacent career.
Most of the online resources/courses for data science are made for the masses and are very shallow in terms of mathematical rigor. Oftentimes the courses do not explain how to choose models, properly tune them or build them efficiently.
From a non-technical background, the challenge of structuring a learning plan for teaching yourself essentially two subjects (math and computer science) and then accounting for the years’ worth of learning, you could have invested in a non-cost prohibitive college program.
Formal education not only provides credential, it provides structured foundational knowledge, hands-on experience, additional career resources.
There’s a lot of talk about data science jobs being high-paying and high-pressure. What’s been your personal experience navigating the industry?
Traditionally, data science jobs are high paying in comparison to non-technical operational roles. Also, keep in mind that data scientist roles in general are often not entry-level roles. I find that companies look for candidates with years of professional experience directly in data science or experience in adjacent fields with abilities to create data science models.
I personally haven’t worked as a Data Scientist in the corporate world yet. Having worked across and with several teams in the fast-paced, high stakes banking industry, intensity depends on the industry, the company, and the team. Roles with higher risks and visible results often have more pressure.
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How do you stay sharp and relevant in a field that’s constantly evolving? Any go-to resources, routines, or rituals you swear by?
I stay relevant by networking- attending tech meetups and technology conferences. Doing this helps me gain awareness about new technologies. They help me to understand how my current skillset aligns. I do remain cognizant of shiny object syndrome though.
In the tech field it is easy to want to catch every new shiny object. This can be counterintuitive and overwhelming in your journey. The new technologies are backed by fundamental principles in math and computer science. I focus on building fundamental knowledge.
This gives me the power to understand and create technologies rather than just being a user of new hyped technologies that tend to drop from the headlines after 6 months.
When building, my go-to resources tend to be YouTube, technical articles, and official Python documentation. YouTube usually gives me a starting point for coming up with new project ideas and applications. While creating my own project, technical articles and official documentation tend to be more helpful and accurate.
If someone wants to break into data science but feels it is “too late” or is overwhelmed, what would you tell them? What’s one thing they can do today to start building momentum?
It’s never too late to invest in yourself and do something you are passionate about!
Do you like math and computer science or are you willing to learn? If the answer is yes, cut out the anxiety by taking a low risk first step!
TODAY, jump into an online introductory Python/R coding course and sign up for a college-level statistics or calculus course for the upcoming semester. This will help you know whether the field may be right for you without an initial large financial or time investment.
Are you dating/married? How do you manage work/life balance?
I’m in a stage where I’m hyper-focused on investing in myself and building the life of my imagination.
Introspection has been a really big part of my life. As someone who is always naturally analyzing, learning, and building, I find it necessary to listen and work with myself.
Sometimes that looks like coding and researching for 10 hours a day. Other days, I’ll spend several hours gardening to replenish. Working with my ebbs and flows overall tends to be more productive and enjoyable.
Also, I practice mindfulness and am very intentional about my consumption – what I watch, eat, and the people I choose to spend time with. This has worked wonders for promoting and protecting my internal balance.
Lastly, are you working on any special projects? Where can readers find you and support you?
As a new founder of Data Swale, a startup tech analytics company I’m working on a couple projects that I’ll put out on my site.
I recently started a Data Swale Blog to take techies and business owners on my founder journey and supply support via data strategy tips.
I’m also organizing and hosting a hands-on Data In Motion Workshop this spring through a local organization called Black Orlando Tech.
Finally, I have a project called What’s Your Mission? highlighting socially minded community members and businesses to promote sharing, learning, and growing for the betterment of our personal lives, society, and planet.
Find and support me by joining my communities below and sharing with one friend!
Site: Dataswale.com
IG: @data_swale
LinkedIn: Data Swale’s LinkedIn | Natesha’s LinkedIn
Business Inquiries Email: natesha@dataswale.com
Site: Whatsyourmissioncommunity.com
IG: @whats.your.mission
