The Northeast Student Data Corps (NSDC) is a community-developed initiative that teaches data science fundamentals to students across the northeastern United States, with a special focus on underserved institutions and students. The Founding Committee of the Northeast Student Data Corps consists of 24 members from different sectors, industries, and professions who have come together to cultivate a community of diverse insights and perspectives.
The Founding Committee is responsible for planning, designing, and launching Northeast Student Data Corps activities in partnership with the leadership of the Northeast Big Data Hub. This is an opportunity to contribute to the creation of a groundbreaking and inclusive new program in data science.
Our Data Science Career Panel webinar series features experts from academia, government, industry, and nonprofits who share their experiences learning and using data science. These virtual events aim to highlight the wide range of educational opportunities and career paths available in data science and data analytics.
Read a recap of the June event with panelists from MassMutual, New York University, and Novartis.
Read a recap of the April event with panelists from IBM, Temple University, Cold Spring Harbor Lab, and the University of Puerto Rico Río Piedras.
Read a recap of the February event with panelists from the World Resources Institute, Rutgers University, and Temple University.
Join the growing global NSDC community!
The NSDC Career Panels have inspired attendees to explore all the career possibilities of data science can offer. Read their comments below!
“What amazed me while listening to everyone’s journey is that all of them started from a different background, whether it was business or computer science, and ended up working in the field related to Data Science. Everyone’s intake and job experience prior and present gives me a reason to consider Data Science a potential career goal.”
“One piece of advice that one of the panelists, Sanjana Reddy Pasnuri, gave that I will remember is ‘choose your job, don’t let your job choose you.’ “
“I believed that the meeting would involve a lot of complex terms and concept implementation of data science, which would be hard for me to understand at the moment as I just started learning about data science. However, it turned out to be very different from what I had thought it to be. At the end of the conference, I feel highly motivated to expand my knowledge of data science.”
Resources for Learners and Educators
Click below to browse Learner Central, Educator Central, and the NSDC Volunteer Video Library, our collections of data science resources for learners of all ages and backgrounds and educators interested in incorporating data science into their classrooms. Resources for learners are broken down by difficulty as well as topics in math, statistics, and programming. For educators in high school, college, or library programs; we’ve included videos, presentations, lecture notes, and code examples from IBM, UC Berkeley, MIT, and other organizations to help you build a comprehensive data science curriculum. The Volunteer Video Library for both learners and educators houses videos on data science topics created by NSDC volunteers, including Columbia University Master’s students. Jump in and see where data science can take you!
Career Resources and NSDC Opportunities
Data science is a growing field with applications in many industries and new jobs being created every day. In Career Central, browse job listings, find tips to make your application stand out, and brush up on your computing and conversation skills so you can ace your next interview.
If you are interested teaching data science to students from underserved communities, get involved with the NSDC! Check out our guide to starting an NSDC chapter in your area and the various volunteer opportunities we have available, from recording a video on your favorite data science topic to designing data science use cases.
Led by Andre de Waal, Frederico d’Oleire Uquillas, and Yusuf Danisman, our Content & Pedagogy team builds a curriculum leveraging academia and industry generated pedagogy and materials to teach data science fundamentals, as well as translational data science with pertinent use cases.
The Peer Instructors team consists of graduate, undergraduate, and post-doc students who will teach data science remotely to students who do not have access to data science programs and play a significant role in shaping the student experience. Team Leaders are Columbia Undergraduates Benjamin Sango, Haleigh Stewart, and Helen Yang.
The Outreach team, led by Forough Ghahramani and Jennifer Oxenford, identifies and enables collaborators interested in engaging the NSDC to increase data science education and knowledge. This includes higher ed institutions, students interested in engaging with the NSDC, and community and government institutions that employ data science, providing real-world examples to teach practical, translational data science.
Dr. Elie Alhajjar is a research scientist at the Army Cyber Institute (ACI) and an Assistant Professor in the Department of Mathematical Sciences at the United States Military Academy (USMA) in West Point, NY, where he teaches and mentors cadets from all academic disciplines. His research interests include mathematical modeling, machine learning, and network analysis. He has presented his research work in international meetings in North America, Europe, and Asia. Full bio available here.
Ajay Anand currently serves as the Deputy Director of the Goergen Data Science Institute at the University of Rochester and brings more than 12 years’ industry experience serving in R&D roles as senior research scientist and technical project leader. Ajay is PI for an interdisciplinary NSF-REU grant focused on combining data science with applications in music and visual media. Ajay also leads outreach efforts to offer data science courses to high school students. Full bio available here.
Catherine Cramer, Director of the Woods Hole Institute, leads the development of tools and programs at the intersection of complex data-driven science, learning, and equity. She has worked on ocean literacy with the NSF-funded Centers for Ocean Science Education Excellence (COSEE), currently focuses on network literacy as co-founder of the international Network Science in Education initiative and co-leads the Data Science for All data literacy effort with the Northeast Hub. Full bio available here.
Yusuf Danisman is an Assistant Professor in Mathematics and Computer Science department at Queensborough Community College, CUNY. He received his Ph.D. in Mathematics at The Ohio State University and worked at the University of Oklahoma before joining CUNY. He is currently working on fractal geometry and its applications to the stock market.
Sarah T. Dunton is the Director of the Expanding Computing Education Pathways (ECEP) Alliance, a National Science Foundation Broadening Participation in Computing Alliance. She develops strategies to increase the diversity of students in K-16 computer science education and career pathways with leadership teams in 22 states and the territory of Puerto Rico. Sarah’s educational advocacy and policy work is informed by the many years she led informal STEM education programs. Full bio available here.
Elena Filatova is an Assistant Professor at the CUNY at Computer Systems department of New York City College of Technology. She is the Director of BS in Data Science program that was launched in CUNY NYCCT in Spring 2020. Dr. Filatova is also a doctoral faculty member in CUNY’s Graduate Center Computer Science department and Linguistics department. Dr. Filatova holds a Ph.D. in Computer Science from Columbia University. Her research focuses on areas of natural language processing and crowdsourcing.
Forough is Associate Vice President for Research, Innovation, and Sponsored Programs for Edge. Forough was previously Associate Director of the Rutgers Discovery Informatics Institute (RDI2), where she led the administration of the Institute and the development of the outreach and educational programs focused on big data and large-scale computing. Her experience in higher education also includes previously serving as associate dean and department chair, new program development, teaching, and accreditation. Full bio available here.
Ahmed Gomaa is the Director of Entrepreneurship and an Associate Professor of operations and information management at the University of Scranton. His research focuses on developing data applications to solve existing problems or improve business functions. He has published research articles in the areas of entrepreneurship, health informatics, business analytics, blockchain, sentiment analysis, and security. Prior to joining academia, Ahmed founded a technology company that uses sentiment analysis for online marketing. Full bio available here.
Leslie LaBarte has been the Seneca District Consultant since January of 2017. The Seneca Library District is made up of Cameron, Elk, Forest, McKean, & Warren Counties in rural Northwestern Pennsylvania. Prior to becoming the District Consultant, Leslie was the Director at the Sugar Grove Free Library. She has her Bachelor's Degree in Business Administration with a Marketing Concentration from Empire State College and a Master's Degree in Library Science from University at Buffalo.
Since 1998, she has been on the faculty at Plymouth State University, first in the Computer Science and Technology Department, and currently in the Communication and Media Studies Department where she is a Professor of Digital Media. Since 2018, she has served as PSU’s General Education Coordinator and has focused on implementing PSU’s Integrated Cluster Learning Model which involves integration and interdisciplinarity, project-based learning, and open pedagogy. Full bio available here.
Kaylea Nelson is a research computing facilitator for the Yale Center for Research Computing, where she assists researchers using high-performance computing clusters and with other research computing projects. Kaylea is also the co-program manager for the NSF Cyberteam to Advance Research and Education in Eastern Regional Schools (CAREERS) Program. Over three years, the program will support 72 compute-intensive projects with RCFs-in-training ("students"), each paired with a mentor, to facilitate research computing needs. Full bio available here.
Thilanka Munasinghe is a lecturer at ITWS with a focus on teaching areas related to Data Science, Data Analytics and Informatics. Prior to joining RPI, Thilanka was the CodeLab instructor at the West Virginia University’s LaunchLab, where he was instrumental in providing technical expertise and mentorship to student entrepreneurs of early-stage student-initiated start-ups. Thilanka’s current research interests are on data-driven analytics using big data to address societal challenges in a diverse set of areas. Link to full bio available here.
Jennifer Oxenford is Director of Research and Community Engagement at KINBER where she is responsible for facilitating collaborations, services, and research support for the KINBER member community. Jennifer leads several KINBER communities of practice including the Collaborative Video Working Group, the Cybersecurity Working Group, and the Research Engagement Advisory Group and also oversees KINBER’s webinars and training offerings.
Xingye Qiao is an Associate Professor of Mathematical Sciences and Chair of the Data Science Transdisciplinary Area of Excellence at Binghamton University, State University of New York. His research interests lie in statistics and machine learning, as he develops and analyzes predictive and inferential tools for complex data problems. Dr. Qiao is also interested in the outreach and educational effort of promoting the awareness of data science ethics, AI fairness, and inclusive and equitable data science.
Aunshul Rege is an Associate Professor with the Department of Criminal Justice at Temple University. Her National Science Foundation-sponsored research and education projects examine the human element of cybercrimes. She intersects theoretical frameworks and methodologies from criminology with hard science approaches to foster innovative and multidisciplinary proactive cybersecurity research. She loves educating the next generation workforce across the social and technical sciences about the relevance of the human factor in cybersecurity.
Benjamin Sango is a junior at Columbia University pursuing concentrations in Chemistry and Economics.
Oshani Seneviratne is the Director of Health Data Research at the Institute for Data Exploration and Applications at Rensselaer Polytechnic Institute. Oshanileads the Smart Contracts Augmented with Analytics Learning and Semantics project and is also involved in the Health Empowerment by Analytics, Learning, and Semantics project. Before Rensselaer, Oshani worked at Oracle, specializing in distributed systems, provenance, and healthcare research. Full bio available here.
Haleigh Stewart is a junior at Columbia University studying Psychology with a special concentration in Public Health.
Fred is a graduate student and Presidential Fellow in the Neuroscience Department at Princeton University. His research focuses on large-scale human brain networks and mechanistic models of how the cerebellum influences the structure and function of the neocortex. Fred works with the Neuroscience Outreach Network to provide k-12 students with access to current and age-appropriate neuroscience educational programs. Before coming to Princeton, he worked as a neuroimaging assistant at Harvard Medical School.
Andre de Waal did postdoctoral research in Logic Programming and Automated Theorem Proving in Germany and Belgium. He then returned to South Africa to take up his position as lecturer in the Department of Computer Science and Information System at North-West University. At the end of 2010, Andre de Waal joined SAS Institute in the US as an Analytical Training Consultant before joining IBM in 2019 as the Ecosystem Data Science an AI Learning University Programs Lead. Full bio available here.
Helen Yang is a junior at Columbia University studying Mathematics, Statistics, and Computer Science.
Tony is a Ph.D. student in Operations Research and Financial Engineering at Princeton. His research focuses on describing credit patterns, their role in forecasting financial crisis, and constructing systems for crisis risk management. As a teaching fellow, Tony orients grad student teachers, develops data science curriculum, and oversees course operations. Previously, Tony led Science Rendezvous Toronto to promote science literacy through outreach initiatives with local schools and the annual festival that attracted 50,000 attendees.
Dr. Emre Yetgin is an Assistant Professor of Information Systems and the Director of the Center for Business Analytics in the Norm Brodsky College of Business at Rider University. His main teaching interests are in Business Data Analytics, Data Visualization, and Management Information Systems. His current research spans the fields of business analytics, computer-aided decision making, human-computer interaction, and computer-mediated communication. Full bio available here.