Mengjie Deng attended the Sept. 10 Math Department event “From Here to Where,” where alumni talk to students about their career path after leaving MIT.
Now a Data Science Manager at Stripe, Mengjie uses machine learning and statistical methods to optimize user experience and business performance for financial products.
Name: Mengjie Ding
Hometown: Shanghai, China
Majors/Minors: Course 14 – Economics; Course 18C – Mathematics with Computer Science
Extracurriculars at MIT: Burchard Scholars; Community Catalyst Leadership Program; Undergraduate Economic Association; Student Representative, Committee on Curricula; Network of Sloan Undergraduate Women
Awards at MIT: Phi Beta Kappa; Meritorious Winner, COMAP Mathematical Contest in Modeling
Achievements Post-MIT: Patent Issued May 2024: Machine learning-based loss forecasting model; Patent Pending: Systems and methods for a transaction processing system offering a service to a user system (Filed April 2023)
How did you use your time at MIT to prepare for your career?
I benefited from the academic training from MIT, through courses in statistics, econometrics, software engineering, and algorithms, as well as career development programs that helped me learn to write resumes and prepare for interviews.
I participated in the Undergrad Research Opportunity Program (UROP) throughout my four years at MIT, through which I gained practical experience in developing software, conducting research with empirical data, and contributing to academic papers.
I explored my career interests and expanded my network through participation in externships during IAP and summer internship programs.
I also found advice from upperclassmen and recent alumni extremely valuable.
What was your first job after graduation, and how has your career trajectory changed since then?
During my college years, I was interested in economic research and financial markets. Upon graduation, I started my career as a researcher in quantitative finance. In this role, I used historical data from financial markets, macroeconomic indicators, and changes in economic policy to build mathematical models to predict movements in financial markets.
After five years of working in the finance industry, I transitioned to tech and became a data scientist. I started as an individual contributor and then became a people manager.
I currently manage a team of data scientists at Stripe. Stripe provides payments services for businesses, and my team uses data science to improve the experience of small businesses that use Stripe for payments processing through better personalization and recommendation. To do this, we use data to analyze trends, generate insights, design experiments and observational studies, and develop machine learning models and time series forecasts.
What advice would you give to current students?
Take advantage of MIT’s academic curriculum and alumni networks. Explore your academic and career interests through hands-on projects, research, and internship opportunities and learn from your experience. Your career is a journey, not a destination; the first job you take up after graduation does not define your whole career, and you can continue to explore your passion, strengths, and growth opportunities along this journey.