People / Students / Class of 2024
Inu Tenneti completed her Bachelor of Science degree in Statistics with a minor in Global Public Health at North Carolina State University. Throughout her undergraduate career, she was involved in various statistics and analytics-related courses, projects, and positions. Her coursework allowed her to acquire knowledge of R, SAS, and Python through projects and classwork. Inu’s undergraduate research work using LINUX to evaluate interlocus gene conversion (IGC) for different tree species was a primary influence in her decision to pursue an MS degree in data science and machine learning at Northwestern University.Despite not having a strong foundation in genetics, she was able to learn more about the field through a statistical viewpoint and the guidance of her mentor, Dr. Jeffrey Thorne. Furthermore, she applied her statistical knowledge in fields such as sports analytics while working as an intern for the Diversity, Equity, and Inclusion (DEI) group at the United States Tennis Association. As a lifelong player and fan of the sport, she gained firsthand experience in the way statistics and data can be used (through Tableau) to evaluate and improve the diversity of players in such a popular sport. Furthermore, Inu interned at VisionPoint Marketing as a data analytics intern. At VisionPoint Marketing, Inu used the Google Analytics platform to gain insights into various social media platforms for higher education clients. She worked with her team to report on the most successful marketing strategies for clients based on her analytical research of the clients’ website interactions. Outside of her academic pursuits, Inu was heavily involved with her co-ed service fraternity: Alpha Phi Omega. She volunteered over 100 hours while working as a full-time student and held various positions on the executive board throughout her time in the organization. She aspires to one day work for an organization that combines her love of service to the community and data science.At Northwestern, Inu is excited to work with her cohort and further expand her knowledge of Machine Learning and strengthen her knowledge of different analytical tools and programming languages.
