Many graduates of the Applied Statistics for Social Science Research program have gone on to pursue successful careers in the field, or are currently studying as doctoral students. All have a passion for using data to answer interesting questions.
Here is a selection of some of our alumni placements:
- Data Analyst, MDRC
- Data Scientist, Bloomberg
- Research Scientist, Amazon
- Data Analyst, NYU Langone Health
- Associate Research Scientist, NYU Global Public Health
- PhD student, Harvard
- PhD student, UC Berkeley
- Research Associate, Guttmacher Institute
- Data Scientist, Teachers Pay Teachers
- PhD student, Stanford
- Senior Data Scientist, Microsoft
- Data Analyst, Center for Policing Equity
- Technical Research Analyst, The Research Alliance for NYC Schools
Read ahead to learn more about several of our recent alumni:
Kenny Mai, ‘21
General Applied Statistics Concentration
What is your current position, employer, and what are some of the main responsibilities you have at your job?
I am currently a Data Scientist at Success Academy Charter Schools. I build a variety of models to answer questions relating to the recruitment and retention of both students and teachers. These models are used for both causal analysis and for forecasting/prediction and are a mix of statistical and machine learning models.
What inspired you to pursue your degree in Applied Statistics for Social Science Research?
Managing NYC Department of Education data for the Research Alliance of NYC Schools inspired me to go back to school to be an analyst rather than an engineer.
How did the program prepare you for your professional life?
A3SR prepared me with thorough and high-quality education on topics that I actually use every single day. Nearly every aspect of the program has been relevant in my professional career, and my knowledge gained from the amazing instructors has impressed both my employers and my peers in the field.
What was something you especially value from your time in A3SR? Was there a course or professor or particular challenge that sticks with you?
I valued my time spent with my professors, second only to time spent with my cohort. Being surrounded by nothing but absolute excellence pushed me even harder and helped me get the most out of my time in the program. All of my classes with Daphna Harel were my particular favorites. She really cares about individual students and is incredibly skilled at teaching.
Prianca Padmanabhan, ‘22
Data Science for Social Impact Concentration
What is your current position, employer, and what are some of the main responsibilities you have at your job?
I am a Data Scientist at NYU Langone. Specifically, I work in the Center for Health Innovation and Delivery Sciences. My focus is on health economics and health policy research, where we use causal inference methodologies to investigate and understand how mechanisms in the US healthcare system differentially impact lower income patients. My responsibilities range from data aggregation and cleaning to data analysis, modeling and interpretation. I have papers published in the Journal of Health Economics and the Health Services Research journal.
What inspired you to pursue your degree in Applied Statistics for Social Science Research
Previously, I worked as a data scientist at a bank. While I was there, I realized the vast potential to use data to make positive impacts on society, particularly for those in need, which I felt was lacking in my role at the time. I decided that I wanted to learn how to develop and implement data methodologies for the purpose of improving experiences for less advantaged populations.
How did the program prepare you for your professional life?
Aside from technical skills, the program taught me a framework of thinking which I use in both my professional and personal life. I learned how to think through a problem by prioritizing the understanding of sources of bias and methods of mitigation. My current role involves analyzing very sensitive data, and the results can hold a lot of weight in evaluating current policies and their impacts on low-income or less advantaged groups. From the program, I meticulously learned the steps of the causal inference framework, how to assess and disclose limitations of research, and how to weigh and uphold ethical considerations through each step of the research lifecycle.
What was something you especially value from your time in A3SR? Was there a course or professor or particular challenge that sticks with you?
For me, the two most valuable classes I took were APSTA-GE 2135 Data Driven Methods for Policy Evaluation taught by Ravi Shroff and APSTA-GE 2012 Causal Inference taught by Jennifer Hill. These two classes taught me how to think critically - specific takeaways were learning how to think through all angles of potential biases and their potential implications, and how to consider and investigate every assumption and limitation that comes with data modeling. I also value the community that A3SR created. It attracts a very special group of people who truly want to learn how to build a mindset (as well as a technical toolbelt) to make a positive impact on society.
Andy Cooke, ‘22
Computational Methods Concentration
What is your current position, employer, and what are some of the main responsibilities you have at your job?
I work as a Data Scientist on the Seller Risk team at PayPal. My main responsibilities center around using internal and 3rd party data to systematically assess the riskiness of companies and prioritize them for periodic underwriting.
What inspired you to pursue your degree in Applied Statistics for Social Science Research?
I wanted to pursue the A3SR program to strengthen my statistical acumen alongside people from a wide range of backgrounds across the private sector, nonprofits, and academia.
How did the program prepare you for your professional life?
Beyond providing new knowledge of statistical models and methods, all courses in the A3SR program share an emphasis on using real world data and practicing high quality research design. These skills are of the utmost importance if you want to generate clear, convincing findings from often messy enterprise data.
What was something you especially value from your time in A3SR? Was there a course or professor or particular challenge that sticks with you?
In my final semester, I assisted in a research project on extending a causal machine learning model to multi-level data. It was really exciting to get a glimpse of the research process and work on a relatively unexplored problem in the field of causal machine learning.
Angela He, ‘23
Data Science for Social Impact Concentration
What is your current position, employer, and what are some of the main responsibilities you have at your job?
I work as a Data Scientist at FreshDirect’s analytics team. I am involved in developing demand forecasts, business insights and data-driven strategies to create better food experience and drive healthy solutions for our community in the greater New York tri-state area.
What inspired you to pursue your degree in Applied Statistics for Social Science Research?
As someone with a background in social science and marketing, I wanted to advance my analytical skill set and bridge the gap between qualitative findings and quantitative approaches.
How did the program prepare you for your professional life?
I think A3SR prepared me well with the ability to articulate data to different audiences. It can be challenging when you go from an academic environment to a place where you work with people without a background in statistics or don’t understand the technical jargon. Being able to communicate the technicals to different stakeholders really prepared me to transition to professional life.
What was something you especially value from your time in A3SR? Was there a course or professor or particular challenge that sticks with you?
I really value the community here at A3SR! I always felt comfortable going to any professor about anything, whether it was for questions about class or career advice. I also made close friends and we really helped each other through assignments, finals, and many other challenges.