From Collateral Manager to Data Analyst: Tahseen Chisti’s Journey Studying Data Analytics
With a bachelor’s degree in both mathematics and management studies from University College London, Tahseen Chisti spent seven years working in finance.
Concerned by a declining need for his role as a credit and collateral manager, Tahseen realized he needed to adapt to remain competitive. “I realized that I needed to learn new skills if I wanted to move into something else, so I started looking up courses in advanced Excel,” he said.
Rutgers Data Science Bootcamp came up when Tahseen started browsing websites on data science. “It piqued my interest,” he said. He liked that it was a six-month, part-time course that allowed him to keep working. So he signed up.
Oscar movie profits, crime rates, and NFL drafts
Tahseen admits that after a full week of working, cooking, and working out, it can be difficult to put in the hours for the bootcamp. Despite the time constraints, he still managed to do the required reading, get his homework in on time, and create three high-quality data analytics projects.
For his first group project, Tahseen and his team wanted to determine the correlation between a movie’s Oscar nomination and its profits. “We wanted to see if it’s worth it for a studio to invest in an Oscar campaign because studios spend a lot of money on winning,” he said. Data insights like these—involving the Oscars and other film awards—are invaluable for producers to know.
For his second and favorite project, Tahseen and his teammates “created a color-coded map of New York that showed crime in the city,” he said. Beyond the attractive visuals, users click to find out detailed statistics, like how much gun crime exists in a given neighborhood.
Tahseen says that the data set can be used to map every city in the world, with real-world implications for awareness about neighborhood safety—and increased funding to safeguard certain areas.
For his final project, Tahseen and his team created a machine-learning algorithm to identify the positions that college football players would likely be drafted in for the NFL. For a multibillion dollar industry like American football, Tahseen added that this information could help teams streamline their scouting process.
Group learning—and pushing boundaries
Working with his fellow classmates taught Tahseen how to collaborate with a group. Beyond creating data sets, Tahseen learned how to discern what each person could do—and then to allot the work in a way so that team members could improve on areas where they were less skilled. In addition, he learned the importance of looking at problems differently—and the value of time management.
After the boot camp, Tahseen landed a promotion. He is now an Assistant VP in Structured Inventory Finance for ABN Amro Capital, a Dutch-based bank, where duties include data analysis. “We’re looking at commodity prices and creating charts and using Excel but moving into Tableau and Python coding—to make the business efficient,” he said.
“If you’ve got a problem coming in, find out what your boss or the client wants, when they want it, and try to find out as much detail about the problem you’re trying to solve before you start tackling it,” he added.
There’s no way around working hard. Tahseen’s advice is to sit down and do the work. “Just put the hours in. Do extra problems, don’t just do the homework, use your resources and really immerse yourself in it,” he said.