Building networks of data science talent

In an era increasingly shaped by artificial intelligence, a fundamental question persists: If advanced tools can perform complex tasks, why must humans still master the underlying principles? MIT electrical engineering and computer science (EECS) Professor Devavrat Shah asserts that foundational skills, particularly in mathematics, remain indispensable. These skills are crucial not only for selecting the right AI tools but also for accurately interpreting their outputs.

“As large language models and generative AI meet new applications, these cutting-edge tools will continue to reshape entire sectors of industry, and bring new insights to challenges in research and policy,” Professor Shah explains. “The world needs people who can grasp the underlying concepts behind AI to truly leverage its potential.”

Professor Shah directs the MicroMasters Program in Statistics and Data Science within MIT’s Institute for Data, Systems, and Society (IDSS). This cross-disciplinary unit addresses the global demand for data expertise through online education. With over a thousand credential holders and tens of thousands of learners globally, the MicroMasters program offers a rigorous yet flexible pathway to mastering statistical fundamentals at an MIT level.

A cornerstone of IDSS’s educational outreach is its partnerships, notably with the Brescia Institute of Technology (BREIT) in Peru. Fotini Christia, the Ford International Professor of the Social Sciences at MIT and Director of IDSS, highlights this collaboration: “Through this partnership, IDSS is training data scientists who are informing decision-making in Peruvian industry, society, and policy.”

BREIT’s Advanced Program in Data Science and Global Skills, developed jointly with IDSS, equips learners with both technical and essential non-technical competencies. Participants complete the MicroMasters in Statistics and Data Science, gaining expertise in statistics, probability, data analysis, and machine learning, alongside critical career skills such as communication, critical thinking, teamwork, and ethics.

Renato Castro, a BREIT learner and credential holder, shared his motivation: “I knew that artificial intelligence, machine learning, and data science was the future, and I wanted to be in that wave.” Having developed data projects across Peru, Panama, and Guatemala, Castro emphasizes the program’s broader impact: “The program teaches more than the mathematics. It’s a systematic way of thinking that helps you have an impact on real-world problems and create wealth not only for a company, but wealth for the people.” Lucia Haro, Manager of BREIT, reinforces this mission, stating the aim is to develop “problem-solvers and leaders” who contribute to economic and social development.

To ensure learner success, IDSS provides tailored support, including regular sessions led by MIT graduate student teaching assistants. Jesús Figueroa, a program completer who now serves as a local teaching assistant, attests to their utility: “These sessions were very useful because you see the application of the theoretical part from the lectures.” Figueroa also noted the importance of learning to effectively communicate complex concepts.

With eight cohorts successfully completed and three more underway, the program has produced nearly 100 MicroMasters credential holders, with 90 more in the pipeline. The IDSS team continually evolves the program to meet emerging needs. Karene Chu, Assistant Director of Education for the SDS MicroMasters, describes a technical assessment tool developed for learner recruitment, gauging prerequisite knowledge in calculus, linear algebra, and Python. Susana Kevorkova, Program Manager of the IDSS MicroMasters, adds that partner input helps tailor offerings, including a new prerequisite “bootcamp” to bridge knowledge gaps.

The program emphasizes hands-on application through social impact data projects with local NGOs. Diego Trujillo Chappa, a BREIT learner, developed a model to understand student retention in graduate studies, improving applicant identification. He now applies these skills to model user experiences in the telecommunications sector. Yajaira Huerta worked on a project to identify areas of highest need for an organization building homes for the homeless during COVID-19, using clustering models and geolocation to optimize resource distribution. “This helped the team to make better decisions,” Huerta noted.

As part of the expanding global IDSS community, MicroMasters credential holders gain access to exclusive workshops and conferences. Many BREIT learners have also visited MIT, engaging with faculty and students and learning about cutting-edge research, including a preview of a new sports analytics course by Professor Anette “Peko” Hosoi. Fotini Christia views this partnership as a model for global expansion: “This partnership is a model we are ready to build on and iterate, so that we are developing similar networks and pipelines of data science talent on every part of the globe.”