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From archaeology sites to Fortune 500 companies, there’s a hot demand for statisticians who can transform quintillions of data into actionable insights. Their expertise in machine learning and artificial intelligence models is crucial to technology, marketing analytics, and other related fields. In finance, they’re sought after for their ability to craft statistical models crucial for analysing risk.
Thanks to the explosion of digital data, there are now jobs, stature, and money in what used to be known as a “boring” field. From 2016 to 2026, employment of statisticians and mathematicians is projected to grow 33%, according to the Bureau of Labor Statistics.
Seeing this immense potential, Jay Li pursued a Statistics degree at Columbia University. And the prospect of getting an Ivy League education fused with the energy of New York City was undeniably appealing.
But it was the programme’s reputation for research and industry connections that truly drew Li in. This being Columbia, both were cutting-edge. “It offers unique opportunities for practical engagement and professional growth, keeping me at the forefront of statistical innovation,” he says.
The ability to transform complex data into meaningful insights is one of, if not the most sought-after skill today. Columbia University’s Master of Arts in Statistics programme provides students with this key expertise, all within the setting of New York City. From machine learning and data science to finance, engineering, and biomedicine, the programme builds technical skills that prepare graduates for a vast range of career opportunities.
Students can select from a wide range of courses in the MA programme in Statistics and specialise in various jobs and industries. Source: Columbia University
There are two key reasons for this: the programme’s longstanding history and its affiliation with one of the nation’s oldest Statistics departments. This rich legacy, combined with a diverse array of courses and mentored research opportunities, ensures that the MA programme remains relevant and competitive in the ever-evolving field of statistics.
“The MA programme in Statistics at Columbia is one of the largest in the US,” says Richard A. Davis, a Professor in the Department of Statistics. “With such a large programme, we can support a wide range of courses that cover most of the areas of statistics that smaller programmes are simply unable to do. Our three-semester sequence in data science, emphasising computational statistics, statistical learning, and advanced machine learning, is a real gem.”
The MA programme begins with three core courses in probability, inference, and linear regression models, followed by six electives, half of which can be taken from other departments. The programme culminates with a capstone course. While students can tailor the MA to their interests and career goals, the curriculum naturally supports four primary learning paths: statistical machine learning/data science, traditional statistical modelling, financial modelling and mathematics of finance, and preparation for PhD studies in statistics or related fields.
“These courses enhanced my knowledge and allowed me to practise advanced techniques, which have been crucial in tackling complex problems in healthcare AI,” Li says. “I had the opportunity to conduct healthcare NLP research in collaboration with Columbia Medical School, which significantly boosted my experience and expertise in the field.”
Columbia University’s MA programme in Statistics is among the largest in the US. Source: Columbia University
In fact, this experience gave him a robust toolkit for his subsequent career as a Data Scientist Manager at Amgen Inc. “The rigorous coursework in machine learning, statistical inference, and experimental design provided me with a deep understanding and practical skills that have been directly applicable to my role,” he says.
Philip E. Protter, Professor, Department of Statistics is not surprised. “Students learn from the textbooks, the coursework, and the teaching of the professors, but primarily they learn from interactions with their fellow students,” he says. “I find the camaraderie of the students is strong, and it is perhaps the best feature of our master’s programme”
The best part? The professors. Students benefit from learning under distinguished faculty members who are dedicated mentors and educators. Many are leaders in their disciplines, having contributed to significant advancements such as the development of likelihood ratio tests by Wald and Wolfowitz in the 1940s, pioneering work on decision theory by Raiffa and Robbins in the 1950s, and ongoing research in probability theory, mathematical finance, Bayesian statistics, and machine learning, with applications spanning epidemiology, bioinformatics, neurobiology, and astronomy.
Pair that with an excellent professional development course, and students are ready to navigate their professional journey with confidence and clarity. The course helps MA in Statistics students grasp the essentials of job searching and career planning. Topics include resume writing, business communication, networking, digital presence, and interviewing skills. Just ask graduate Laura De Los Santos.
“The support I received for my professional development as a student was essential for my career journey,” she emphasises. “It encompassed a wide range of topics, from application strategies to negotiating compensation packages. The flexibility to take more applied classes from the Computer Science department was invaluable in preparing me for the industry, alongside the foundational knowledge of classical statistics.
Another graduate, Yayuan Wang, a data scientist in the global equity research department at Neuberger Berman agrees. “I learned about the hiring information for my current position through career news shared by the Assistant Director of Career Development,” says Wang.
Interested? Apply to the MA in Statistics today.
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