Whew! My #BlackInDataJourney was not linear at all. I for sure had to do a ton of soul-searching to understand what I wanted. I THOUGHT I’d do undergrad as a bio premed major but I ended up changing my mind a lot before finding my for computing! Buckle up!

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As a bio pre-med major, I had absolutely no clue of what I wanted to *actually* do. Fortunately, an aunt of mine told me to look out for “genomics” and “bioinformatics”. I didn't know what those words meant at the time. But it was a lead!

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I hit the ground running looking around for “genomics” or “bioinformatics” majors/classes that first semester but they didn’t exist for undergrads yet. Much of what was offered was exclusively at the grad school level (this was in 2015).

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Soon, I realized I wasn't enjoying my biology courses & that I should switch majors. Part way through the year, I stumbled upon the Bachelor's Degree with Individual Concentration (BDIC) program. It was essentially the “build-a-major” program @UMassAmherst.

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Since the genomics & bioinformatics table didn’t exist yet, I tried to build it as an informatics major @umasscs. The major was being incubated in BDIC (it officially became a major in 2019) & allowed flexibility. I availed myself of that to explore computing

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SB: Something that BDIC majors could do was come up w/ a title for your major that reflects the curriculum you piece together throughout undergrad.

I'll drop a emoji each time I changed it I essentially "switched majors" every time I switched up my curriculum.

Throughout my early data sci. experiences (& later on), I was overwhelmed in courses, conferences & meet-ups where I was often the only Black student w/o a formal CS/math background. I had long chats w/ mentors b/c I felt like I didn’t belong in those spaces.

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I quickly realized the need for community & found friends+profs willing to support me! I also joined the STEM Ambassadors Program (STEM AP): it focuses on upping participation in STEM among underrepresented students (5yrs later, I'm a grad mentor in STEM AP)!

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It was through STEM AP that I landed a grant to work in a lab over my freshman summer. I didn’t know where I’d end up or what my career goals were just yet, but I knew the experience would help me find out.

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Ultimately, I was paired with a computational biology lab that had a focus on evolutionary genomics/bioinformatics! I spent 10 weeks with them that summer and then I was asked to return for paid fellowship opportunities!

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It was EYE-OPENING! Day by day I learned R, wrapped my head around data science re: bio, & got a love for coding that my CS courses couldn’t give me through HW. It was through my lab's support & mentorship that I knew I could pursue a career in computing.

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But it was also then I realized that bio. research didn’t have my like I thought! I believed bio could still work so I stuck with that. All I knew is that I wanted something different. So I applied to a data sci REU opportunity my soph yr to test the waters.

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As I looked ahead at job postings, I latched onto what was being asked for to help shape my curriculum and understand what I'd need to do to be qualified. Statistics came up frequently before I genuinely understood how it factored into a data science career.

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That summer, I worked with the Expanding Computing Education Pathways alliance under an NSF grant. I was focused on improving their website’s UX/UI. It wasn't explicitly data science, but little did I know, data scientists wear many hats in their careers.

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They asked me to come back too on new NSF grants! This experience helped to solidify my for the viz & communication aspects of data sci. It was also the first time I worked w/ stakeholders as I balanced their interests with the implementation of my projects.

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As senior yr began to heat up, I had to make a decision. Bio or nah? Pre-med OR NAH? I ended up dropping bio. But I held onto the pre-med track. I STILL wasn't sure. As a first-gen Haitian-American, I could *FEEL* the pressure to be a doctor anyway

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But I didn't.

Instead, I embraced my interests even harder! I decided to do an honors thesis that incorporated everything that I had learned. I carried out indep. projs. I took on a peer mentorship position to guide students like me. I pivoted when I could.

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I took every offline/online course I could, read every book that had a free PDF version for students , and researched every aspect about careers in the data science industry. I didn't feel confident about DS until I turned around and saw how far I came.

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I ended up finishing undergrad with the pre-med track completed & absolutely zero interest in going to medical school But what I did know was that I had a spot in data science. And I forged it with the help of my village of supporters, sponsors, & peers.

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In my current jr. data scientist role, I've helped restructure an enterprise database, contributed significant efforts to financial dashboards, and worked behind the scenes in web development. Recently I've been carrying out efforts in algorithmic underwriting.

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As I look back, I don't even feel like I've scratched the surface in terms of what I can do and learn. Right now, I'm pursuing an M.S. in CS to keep my eyes open. I'm also trying to incorporate as many indep. projs. as I can to keep my full.

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Everything I do now was made possible by the twists and turns I took during undergrad. Had it been a linear journey, I doubt I'd be here or necessarily know where my interests are. In retrospect, it was 100% worth it.

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So here's all my majors/titles

(1) Biology
(2) Informatics
(3) Biology & Informatics
(4) Informatics & Biostatistics
(5) Leveraging Medicine Through Informatics & Data Science
(6) Informatics & Data Science

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TL;DR: Lessons
+ Branch out as far as you can! Figure out what you hate/
+ Speak to profs, interview them even! Determine if their areas of focus resonate with you.
+ Look ahead at job postings to help guide your journey.
+ Hold onto what you tightly!

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