Data analytics is an essential tool for businesses looking to thrive in today's data-driven landscape. It can empower organizations to make smarter decisions, optimize processes, understand customers better, and gain a competitive advantage in a rapidly evolving environment.
Successful data analysts also need to be strong communicators, a skill emphasized in the Kogod MS in Analytics program. Professor Virtu, an American University alumna of the math and computer science program, knows this firsthand. As she approached her own undergraduate graduation, she caught wind of the master's program and decided it was right for her.
Virtu first became interested in data science when she studied computational science in undergrad. She liked that the field played to her technical strengths in statistics and programming, while also maintaining creative freedom through problem-solving and storytelling.
In the program, professors teach students math theory and hard technical skills while also translating them into a business setting. “Professors really bridged the gap between theory and practice. We learned how complex theories could apply in actual jobs, especially ones that weren’t just research-based,” said Virtu.
Professor Virtu emphasized that communications were a key focus of the MS in Analytics program. Every time students had to write a brief, Virtu said she was challenged to cut it down by half. Students were encouraged to think about how their C-suite audiences and other high-level stakeholders would receive the information, and she and others learned how to succinctly articulate key points.
After graduation, Professor Virtu’s career led her to work with a lot of pre-IPO tech companies, including a few software-as-a-service startups. Because the companies were in such early stages, she wore many hats—from doing a bit of marketing to a bit of sales. But most of all, she focused on data and applied her high-level analytical skills to solve organizational challenges and make effective business decisions.
Since Virtu spent the majority of her data science career working for SaaS companies, the most common business questions would reveal insights into their financial levers. She was often tasked to use data to find ways to reduce customer churn, increase customer lifetime value, fine-tune market segmentation, and optimize lead funnels. Additionally, she has been asked to develop fraud detection models and recommendation systems.
“I would create databases, analyze the data, then produce operational plans like how we could get companies to increase their revenues by X percent or Y millions of dollars. Then, we could execute those plans,” Professor Virtu said.
Her analytics work taught her to approach data analytics with persistence and curiosity.