These essential positions are very lucrative “top jobs.” Meet two Arkansans who already know the perks of these professions.
Melissa Pizza is a data analyst.
She graduated from Hendrix College in 2019 with an economics degree and loved using logic, theory and data to answer questions and solve real-world problems.
“I fell in love with the collection and organization of data resources to answer questions while writing my undergraduate thesis,” Pizza says. “I collected the raw data, transformed it in a way that was usable, and then used statistical modeling to answer the question: ‘Can bats be used as a natural substitute to chemical pesticides?’”
After she graduated, Pizza knew she wanted to work with data but wasn’t sure exactly how. She networked with local data analysts and scientists and met a business analyst who convinced her to pivot to data analytics. The analyst explained how C-suite professionals and other business owners used to rely on their “gut” to answer their business questions, but with the development of big data, professionals now use data to support or refute those “gut” decisions.
“Data analysts are often the middleman between engineers, scientists and business leaders,” Pizza says.
After speaking with a few First Orion analysts who went through the company’s apprenticeship program, Pizza says she was drawn to the culture of peer mentorship and the “fall fast” philosophy the company’s leaders embodied. She worked her way up from data analyst to team lead.
“When I look at people who are the most successful in my field, they are naturally inquisitive,” Pizza says. “They are the type of people who aren’t satisfied with an answer unless they understand how the person got [there]."
Jason Yingling is a data scientist.
In this role, Yingling works at the intersection of statistics, scientific methods, artificial intelligence and data analysis for First Orion. Data scientists are at the cutting edge of technology and work on some of the most challenging and exciting projects in tech. Some examples of the work these tech professionals do include helping create Facebook’s face recognition, Netflix movie recommendations, self-driving cars and texting autofill and autocorrect.
“Growing up in Arkansas, I was never really exposed to data science as a career,” Yingling says. “As a kid, I was always fascinated with the thought of artificial intelligence and loved working with data. After my time in the Navy, I went to the University of Central Arkansas as a math major."
"My first exposure to data science was when I got a dataset for the Little Rock Housing Market and created a model to predict the price of houses,” he says. “I had a lot of fun with that, but I was not completely sold until I had a project where I was given data on blood drives and predicted if an individual would donate at a blood drive. I absolutely loved the thought of being able to get insights and make predictions given a data set.”