When Shaked Shtauber wanted to find out if there really is a police bias against minorities and if so, which communities are most at risk, she knew exactly where to start.
Her bachelor’s degree in bioinformatics had prepared her well — as had her experience at Columbia Engineering FinTech Boot Camp. For her most recent endeavor, she knew she’d draw on the skills learned while working on her three boot camp projects.
All about the data
Shaked’s first two boot camp projects used data and machine learning to predict real estate and stock market prices, respectively. In the first, she and her team analyzed data from the last three years to predict New York real estate prices across each of the five boroughs.
In the second, they experimented with different machine learning algorithms to find the most accurate way to predict whether stock market prices will increase or not.
Shaked was already familiar with coding and data analytics, but putting those skills into practice helped solidify her knowledge.
“I learned that you need to have a good data set,” she said. “If you don’t, the project won’t turn out, because everything relies on the data.”
But her team’s last project was different. They used a programming language called Solidity to create a blockchain marketplace for private flights, which they called JetChain. This platform would allow users to register for private charter flights around the world, removing the need for flight brokers and putting control back into the hands of jet owners.
Before the boot camp, Shaked was familiar with languages like Python and SQL, but Solidity presented a new challenge. “It was a completely new language for me,” she said. “Learning Solidity in a short time was hard. But we had great instructors who were always there to help.”
A team effort
Her team members helped, too. Shaked enjoyed wearing a variety of hats throughout her projects. “In every project, I played a different role,” she said. “Sometimes I led, sometimes I stayed on the coding side. But it was always a group effort.”
When her team members needed help coding, Shaked coached them over Zoom. In fact, the remote nature of their collaboration brought an interesting dynamic to each scenario. “The whole experience was remote,” Shaked said, “and there were pros and cons to that.”
Despite the challenges, the satisfaction of seeing a project through to completion paid off every time. “I really liked working on the whole process, from start to finish,” Shaked said.
Applying coding to machine learning
After the boot camp, Shaked didn’t hang up her coding hat. On the contrary, she completed two new projects on her own.
The first used machine learning to predict the likelihood of death in patients with heart failure. “Bioinformatics is computer science with a lot of scientific subjects like genetics and biology,” she said. “So in my bachelor’s I learned a lot about medical subjects. That’s where this idea came from.”
The idea for her second project came from current events. “Because of everything that’s happened in the last few months, I decided to use analytics in Tableau to analyze police shootings. This project was specifically to sharpen my data visualization skill in Tableau, a skill every data analyst needs to have.”
Shaked created an interactive chart showing the data for police shootings of white, Black, Hispanic, Asian, and Native Americans.
Users can filter the data by race, gender, age, state, and other factors. They can also view data on body cameras, weapons type, and whether or not the victim was fleeing at the time of the shooting. Shaked said it was interesting to see all the data come together.
Onward and upward
Shaked has received great feedback on her projects so far, from both friends and industry professionals. Now, she’s working on her biggest project to date: a job as a data technology analyst at Keyrus. “It’s an amazing workplace and I’m learning new tools every day,” she said. “Soon I’ll start working on my first project.”
Interested in a new career? Learn more about Columbia Engineering FinTech Boot Camp today.