68 Breaking into tech: black girl edition

Woomy Michel

68.1 Background

Hi, my name is Woomy Michel 👋🏼 and I’m here to share my story as a Black girl in tech. I am the first-born child to Haitian immigrants, an alumna of the Illustrious Clark Atlanta University (goooo Panthers 🐾♥️) and a current data science grad student at Columbia University. I am the first in my family to attend and graduate from college, as well as attend grad school. In this short book, I’ll be sharing my honest journey, tips, advice and ways for you to break into tech.

To be honest, when I’ve read a “breaking into tech” article, the story never resonates with me. Whenever I read a piece, it’s told from the perspective of someone who’s classed, well-resourced or has industry connections. This always comes off as impersonal given I grew up the complete opposite.

Oftentimes, I (emphasis on the “I”) feel like people tend to share the good parts of being in tech, without ever mentioning the bad and ugly. Social media honestly creates a false sense of reality. Everyone thinks that tech is extremely easy to break into and all roles pay $100k or more which is false. Don’t get me wrong, there’s definitely some roles that are easy to get into and some pretty high salaries, but that’s not everyone’s truth, especially not mine.

For me, transparency is a big thing and knowing the full story before diving deep into the waters of the unknown is important.

68.2 Finding My True Calling

I started off undergrad as a dual-degree engineering major. The program was geared towards students who wanted two bachelor’s degrees: one in their engineering discipline and one in their natural science discipline. At the time, I was majoring in math and biomedical engineering. I thought I was going to be a biomedical engineer. I mean, what else could I pursue as someone that was extremely passionate about mathematics? Engineering was the only field people told me I could go into with a math background.

I tried the engineering thing my freshman year and honestly…I HATED IT! It didn’t help that my engineering professor would go out his way to belittle me in class some days. There was no type of support in the program, no tutors and not much help from the professor either. Despite hating the engineering department, I wanted to stay in the program because I knew I belonged there. I mean, I was getting good grades and understanding the material, why wouldn’t I have stayed? Little did I know, the program would become severely unbearable 😅. And by “severely unbearable”, I mean my classes would become significantly harder and bring me severe unhappiness. Your girl was depressed and stressed.

Being a miserable engineering student wasn’t it for me anymore. I knew at heart that I was a math girlie, but was very unsure of what I wanted to do. Second semester, I took a programming class that I really enjoyed. It was the first time I was taught a computer science class by another Black woman since middle school. Seeing the similarities between coding and math made me think of the ways I could apply math and comp sci together.

Computer Science and Mathematics complimented each other so well. Programming was so natural to me because it was methodical, analytical and catered to my problem solving skills much like math. Coding was a huge jigsaw puzzle to me; writing chunks of code and doing constant debugging (#lots of comments#) to figure out which lines of code returned an error. Tracing code constantly and rearranging chunks too. It never felt tiring, it was something that happily kept me up at night.

By the end of freshman year, I had completely changed my major to Mathematics and added a minor in Computer Science. It felt like a burden had been lifted from my shoulders once I left the engineering program. I was finally doing something that I was passionate about and had fun doing. Being affirmed by Black faculty that I was capable and belonged in the STEM community was exactly what I needed.

68.3 Oh…Technical Interviews️ 😅

I feel like the trajectory of my career changed after technical interview season. After completing my first programming class, I thought that software engineering would be the perfect route for me. Alas, the whiteboard interviews would be an extremely humbling experience for me.

Now, most roles that you interview for mainly ask behavioral questions to see if you’re the ideal candidate. However, when it comes to the tech industry, there’s a behavioral interview followed by several rounds of technical interviews. I never was able to get the hang of them, to be honest. Something about a HackerRank interview was just so nerve wracking to me. I knew how to program, but I couldn’t solve two coding assessments in an hour no matter how well I prepped. On top of that, the way the interviewer would frame the questions was weird. I’d never understand what they were asking until after the interview because the questions were asked in the most convoluted way possible. One thing I’d always do when stumped was ask clarifying questions so I could gauge how to solve the problem, but even then…it wouldn’t click in my brain until the very end of the interview. You know that feeling when you’re taking an exam and you’re stuck on a problem and finally remember how to solve it, but it’s too late? That was me.

After bombing nearly all of my technical interviews, I decided to take a step back and think of other tech routes that I could possibly see myself in. Low and behold, data science was what I came across thanks to the CAU Math department.

Spring semester of my sophomore year, I took an Intro to Data Science and Data Engineering class that I really enjoyed. You know my programming professor always mentioned that once you know one programming language, you can learn another. She was right, I just had to get adjusted to the syntax. RStudio was very similar to Python, they were like cousins (for the most part). RMarkdown was the hardest thing in the beginning because I didn’t know how to knit my document.

Since discovering my new found interest, I’ve had the opportunity to: - conduct data science research with the National Science Foundation (NSF) and ERASE Child Trafficking - presented research at the National Association of Mathematicians (NAM) MathFest XXX and the Academic Data Science Alliance (ADSA) Spring Meeting 2022 - interned at GoFundMe as a data analyst - and so much more!

I’m so grateful that I didn’t let technical interviews deter me from following my true passion. Sure some days were hard, but I never let that stop me from pursuing a career in data science. My failures always served as a learning experience for me. Always celebrate your losses and most importantly, it’s not how you start, it’s how you finish.

68.4 Tips for being in Data Science

Here’s a bit of advice from me if you want to get into data science:

• The possibilities are endless, don’t stick to mainly STEM work for data science. Data science and tech lie at the intersections of multiple industries. I have friends who’ve studied migration patterns using data science techniques. You can do anything in this field!
• Take some time to learn Python, R and SQL. I promise you, the more languages you know, the better. Plus, it makes you more marketable ☺️.
• You do not have to be a CS major to be in data science! Data science can be applied to any field of study. From the social sciences to the natural sciences.
• Apply to summer internships in the fall! Whether you want to do research or industry, start looking for roles early on. Handshake is a great tool for finding internships and research opportunities.
• Network, network, network! You never know who could open doors for you. Knowing someone goes a long way sometimes. Always ask for help! Closed mouths don’t get fed.
• Take some CS classes like Data Structures, Databases, Introduction to Programming, etc. This will help you learn the fundamentals.
• I can’t stress this enough, do what makes you happy! I know a lot of people will tell you to go where the money is, but your peace and happiness is worth so much more in the end.

68.5 Affirmations for Black Girls

Last, but not least, some affirmations. Tech can be tough for us sometimes, so here’s a little something to get you through your rough days:

• I am loved
• I belong here
• I am deserving
• I am enough
• I am confident
• I am smart
• I am valid
• I can do this
• I am brilliant
• I am not alone
• I am worthy
• I am intelligent
• I make time to take care of myself
• I am gentle with myself and my mistakes
• I am capable of doing anything I put my mind to
• I deserve nice things, everything I desire is within my reach

Remember this industry needs you and you worked hard to get here!

68.6 Resources

These are some of my favorite resources for folks that want to learn more about computer science, data science, programming, building community in tech, etc:

https://www.geeksforgeeks.org/ (one of the best CS sites ever for learning programming, data structures and doing interview prep)

https://www.youtube.com/c/GeeksforGeeksVideos (the GeeksforGeeks YouTube channel)

https://hbcu20x20.com/ (Black job network, ample opportunities for mock interviews, etc)

https://leetcode.com/problemset/all/ (tech interview prep)

https://www.udemy.com/ (ample free courses!)

https://www.edx.org/ (the perfect resource for data science and data analytics)

https://www.colorstack.org/ (a tech organization for Black and Latinx students)

https://experience.afrotech.com/ (one of the best Black tech conferences)

https://www.renderatl.com/ (one of the best Black tech conferences)

https://drive.google.com/file/d/18q40D9Gws-H7IvXcS0ZERJsuZ-FYfcHz/view?usp=sharing (link to Python textbook)