Minghan Liang, MPS ’22, followed his curiosity. After about two years spent in the technology industry getting valuable experience with data science and artificial intelligence (AI), Liang decided to expand his understanding of statistics and enrolled in Cornell’s Master of Professional Studies (MPS) in data science and applied statistics program. The one-year master’s program is intended to equip students like Liang with the modern data analysis skills every field needs. Today, he’s a data scientist at Chewy, a leading pet care company.
Where are you from, and why did you decide to pursue an MPS degree?
I’m originally from China and completed my undergraduate degree in financial mathematics at UCLA in 2019. During that time, I witnessed the surge of big data and the rapid evolution of machine learning and AI. As I took courses in applied mathematics, statistics, and machine learning, I realized how much I enjoyed using scientific tools and programming languages to tackle real-world problems. I was drawn to the idea of uncovering insights and patterns from data to make meaningful contributions in the business world.
After working in the technology industry for about two years and gaining experience with big data, data science, and AI, I wanted to deepen my knowledge of statistics, which I see as fundamental to modern machine learning. That goal led me to pursue a master’s in statistics at Cornell, where I joined the MPS in data science and applied statistics program to solidify my expertise in scientific programming and data technology.
What was your experience like in the MPS program, and what are some skills you took from it?
My experience in the Cornell MPS program was rewarding and fast paced. I successfully strengthened my knowledge in statistics, machine learning, and programming as I had hoped. My accomplishments include:
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Deepening my understanding of probabilities, statistics, and statistical learning through advanced coursework and real-world applications.
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Gaining a solid grasp of the theoretical foundations and computational techniques behind both classic and cutting-edge data science models.
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Expanding into emerging AI domains like natural language processing, deep learning, and reinforcement learning, which are shaping the future of data science.
Can you tell us about your current job?
I am currently working as a data scientist at Chewy, the leading U.S. e-commerce company specializing in pet supplies, pet healthcare products, and veterinary services.
I support the pet health business vertical of the company, working closely with various business product/project teams to utilize data science and AI technologies to drive better business decisions (internal facing) and enhance customer experience (external facing). Some of my past and present work tackles subjects such as product recommendation, customer segmentations, and customer propensity/churn analysis.
In what ways did the MPS prepare you for your current job?
The MPS program strengthened my foundations in probability, statistics, and machine learning, which are essential for the analytical and modeling work I do daily. Additionally, I gained more practical skills in Python and SQL through the program's diverse coursework, both of which are critical tools in my role.
What advice would you give to new students in the program?
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Take the time to master all core MPS coursework, even if you have studied them before. Understanding the derivations and reasoning behind formulas – not just the conclusions – will make a significant difference in applying these concepts effectively in industry roles.
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Make the most of Bowers CIS’s extensive resources. Dive into advanced topics in computer science, AI, and statistics to build a versatile skill set that will set you apart in the job market.
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Fully leverage available career resources to the best extent. This includes connecting with alumni and conducting informational interviews, practicing mock interviews with your peers and career advisors, and proactively participating in career events designated for MPS students, like workshops, information sessions, and alumni talks.