Alumni

Through the MSAS program I gained new statistical and computational knowledge and skills that broadened my understanding of the data that I work with, and provided me with methods for generating conclusions from those data. The program helped me become a more competitive candidate for PhD programs in my field with newfound experience applying these methods to my own research, publicly available datasets, and those provided by course instructors throughout.

The Applied Statistics program at Teachers College helped build the foundational statistical knowledge I needed to succeed in my current role as a data scientist at the NY Fed. For instance, I have used concepts in statistical inference, computational statistics, linear modeling, machine learning and data visualization so far in my post-grad career. In addition to the curriculum, academic mentorship played a tremendous role in shaping my career and research interests as a statistician. Additionally, the flexibility to engage with the larger Columbia community allowed me to tailor my studies to my interests and presented TA and full-time work opportunities as well.

Before starting in the MS Applied Statistics program at TC, I was determined to enter a PhD program for Clinical Psychology, but after taking courses in the MSAS program, I found my true passion in statistics and data science and quickly redirected my educational journey. Since graduating in 2016, I have worked in educational research in the California Community College system, applying methods of data science, predictive analytics, causal inference, and structural equation modeling (and hopefully one day, machine learning techniques) to build and analyze educational data. Currently, I lead a team of researchers at SCCD on projects that focus on testing and improving initiatives and programs that increase access and support for students in higher education, especially for underserved student populations. In addition, I have been building foundational infrastructure for sustainable database management, data sharing between local institutions of education, financial planning projections, and data visualization suites for faculty and administrators at the college.  

The MS Applied Statistics program at TC was an invaluable opportunity for me; the instruction was current and advanced, the faculty were encouraging and positive mentors, and the courses were designed to include assignments and projects that directly translate to employable skills. Not only did the program set me up to be successful in my current role, but it also allowed me to cultivate and live my passion for data.

I enrolled in the program after a lengthy career as a software developer. I was looking for a change, and fell in love with statistics upon taking an Introductory class in Columbia’s Continuing Ed program. I loved being back in school, the TC professors were wonderful, dedicated teachers, and the curriculum introduced me to a wide variety of statistical methodologies. I found the math difficult but the programming easy (others had the opposite experience!)

Since graduation, I’ve been a biostatistician at Columbia University Medical Center supporting the bone endocrinology group. I’ve employed linear and logistic regression, ANOVA, and linear mixed models to analyze randomized multi-year longitudinal studies assessing the efficacy of drugs treating osteoporosis. In addition, I’ve tutored students and helped provide analysis for students on their dissertations. I continue to study independently and consult with a wonderful online subscription company called The Analysis Factor.

I lead a team of highly technical engineers and data science professionals who provide free strategic consulting services as well as paid technical implementation services to global agencies. These customers use our technology to manage their complex programmatic advertising buying, among other things. The Applied Statistics program at Teachers College prepared me for this job by helping develop the technical skills and strong statistical knowledge needed to manage such a highly specialized team.

While I don’t actually do much customer-facing analysis or technical implementation work myself, I often need to quickly assess other people’s work and give thoughtful feedback and guidance about future directions, skills I would not possess without my time at TC. I am particularly pleased with the Applied Statistics program’s emphasis on integrating R into many of our classes and assignments, which gave me knowledge that has helped build credibility with my team and with our customer contacts, who are often VPs of Analytics. In addition, I was able to take Python classes at other schools within the broader Columbia community.

Finally, I pursued my graduate work while working full time in a similarly demanding role at Adobe Software. During this time, not only did I often need to travel during the week for work, I also had unpredictable, last minute work emergencies that required I miss a scheduled exams and classes. The professors at TC were always flexible and worked with me to ensure I got the most out of the program.

I work with a team that builds recommender systems at Ebay. In my current role as quality engineer, I use statistical knowledge I learned in the Applied Statistics program at TC, such as modeling, machine learning, data analysis, and data visualization to validate and ensure the quality of products meet standards. In addition to what I learned in the TC program, the elective courses I took in other Columbia schools also benefited my career development. Besides the curriculum, I also gained a lot of experience in teamwork, plan management, and communication skills during my time at TC, which helped me succeed in working with an agile team with high momentum.

Being in love with using statistical techniques to analyze big data and provide innovative solutions, I came as an international student from China and studied in the Applied Statistics program at TC. I really enjoyed the courses and the training provided by the program, which I believe counted a lot for the professional opportunities I received. I developed a solid statistical and mathematical foundation through the probability and statistical inference courses. The practical labs and assignments improved my proficiency with the application of a wide range statistical techniques and software. The guest lectures and workshops I attended also gave me good insights about how working in this industry looks like.

As a current Business Insights Manager working at the advertising department under a U.S. cable television company, I am responsible to lead a team for customer analysis projects to derive business insights. The ability I obtained from the Applied Statistics program to utilize multiple statistical tools and clearly communicate results of statistical analyses helps me improve the business delivery efficiency at work. Moreover, I really appreciate presentation opportunities I had in classes at TC, which prepared me to become an instructor at NYU.

When I applied to graduate schools, my goal was to expand my skills in quantitative analyses so that I could work in social science research. TC’s Applied Statistics program allowed me to achieve this goal by providing an invaluable opportunity to study modern statistical techniques and immediately put them into practice through course-related projects and through the abundant research opportunities in the Columbia community.

In my current position, I am a mixed methods education researcher and act as the primary quantitative analyst on several evaluations, employing many of the techniques I learned from TC. I often co-lead research design development, analyses, and dissemination efforts for various clients, including state education agencies. The skills I gained from TC have been vital to my work and my ability to communicate complex analytic results to clients.

I decided to pursue the MSAS after years of working in the private sector and development policy consulting. My goal was to acquire sound quantitative knowledge in impact evaluation and statistical analysis to serve my country better by working alongside the government and offering top-notch services to my clients. The program provided me with the techniques I was looking for and helped me hone my knowledge of the computational tools required to apply the methodologies learned. As an incoming public servant, I am now more confident in employing causal inference and evaluation methodologies to assess the effect of policies enacted in my country.