Featured Member: Aquilah Daughtery on HBCU CONNECT!

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Q&A With Aquilah Daughtery

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Aquilah Daughtery
Competition Team Member, North Carolina A&T State University
Location: The Woodlands, TX United States
Joined: Jun 20th, 2018

About (request update)

Experience

I currently work with North Carolina A&T State University as Competition Team Member
I have years of experience working in the industry.

Competition Team Member | North Carolina A&T State University
From October 2024 to October 2024 • 0 year(s)
Key member of HBCU student team that invented and presented BYTEBack, a sustainable e-waste management initiative, earning first place at the I3 MSI Business Competition. Devised a circular economy business model to provide affordable refurbished technology to underserved communities within a 48-hour timeframe.

Data Science Intern | Georgetown University Math Department
From May 2024 to August 2024 • 0 year(s)
One of two programmers who developed a stock portfolio analytics tool using Python and R to forecast stock performance, achieving up to 82.5% adjusted R-squared accuracy. Gathered data, validated model accuracy, and analyzed key financial metrics including EPS, market cap, and P/E ratio.

Data Science & Analytics Trainee | North Carolina A&T State University
From August 2022 to May 2023 • 1 year(s)
Applied linear regression, random forest, and XGBoost algorithms in R to predict the popularity of quotes from the Goodreads website under mentorship of an NCAT Data Scientist and two Ph.D students. Improved skills in R programming, project visualization, and collaboration.

Research Assistant | Tulane University Math Department
From May 2021 to July 2021 • 0 year(s)
Used NetLogo multi-agent modeling to study the relationship between milkweed availability and OE parasite death rates in monarch butterfly populations, finding that less milkweed correlates with higher butterfly mortality. Presented findings at the Xavier Research Showcase.

Research Intern | American University Math Department
From May 2020 to July 2020 • 0 year(s)
Worked with data scientists to identify environmental and social factors predictive of COVID-19 case and death rates in New York City, co-authoring a paper published with the National Library of Medicine. Presented findings to the NSA.

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