Adam Hearn

Data Scientist / Researcher

American Institutes for Research


I am a data scientist at the American Institutes for Research, where I support the Data Science and Advanced Analytics group in conducting cutting-edge research on topics related to education and public policy. My research emphasizes computational social science, machine learning, natural language processing, causal inference, and data visualization, using tools such as Python, R, Stata, and Tableau.

With a master’s degree in Data Science for Public Policy from Georgetown University and a bachelor’s degree in economics from Rhodes College, I have the theoretical and practical knowledge to apply data science methods and techniques to solve real-world problems and inform policy decisions.

As a passionate sports enthusiast and skilled data scientist, I harness my mathematical expertise to develop sophisticated models for predicting outcomes of MLB and NBA games. By leveraging historical player and betting market data, I create intricate algorithms that capture the nuances and complexities of these sports, enabling me to generate predictions for these events.

My mission is to leverage my data science and technical skills for the public good.

CV can be downloaded here.


  • Computational Social Science Research
  • Applied Machine Learning
  • Statistical Computing


  • MS in Data Science for Public Policy, 2021

    Georgetown University

  • BA in Economics, 2019

    Rhodes College










Data Scientist Associate

American Institutes for Research

Jun 2022 – Present Arlington, VA
The American Institutes for Research is a behavioral and social science research, evaluation and technical assistance organization whose mission is to generate and use rigorous evidence that contributes to a better, more equitable world.

Director of Institutional Research & Data Analytics

Franklin College

Feb 2021 – Jun 2022 Franklin, IN
Franklin College is a residential, open-access liberal arts institution located 20 minutes south of Indianapolis. A Franklin College education fosters independent thinking, innovation, leadership, and action for ever-changing professions and a globally connected world.

Data Scientist & Database Administrator

College Transitions, LLC

May 2018 – Present Charlotte, NC
A team of consultants, researchers, and former admissions officers, College Transitions offers a data-driven program of services that helps students identify good-fit schools, maximize their admission prospects, and make the most of their college investment.


The Generalized Synthetic Control Method: A Powerful ML Algorithm to Produce Counterfactual Estimates for Experimental Data

This post will cover the Generalized Synthetic Control method, a ML algorithm that is lesser known within Data Science circles.



Do institutions serve their geographic constituents? Evidence from student migratory patterns

This RShiny web-app provides a resource for higher-ed stakeholders and researchers to investigate migration patterns of postsecondary learners.

The Higher-Ed Coronavirus Response in the Public Sector

Using data form the College Crisis Initiative, this project discusses the usage of dimensionality reduction techniques and feature importance algorithms to analyze fall re-opening plans.

Isolating the Mechanisms Behind the Test-Optional Admissions Policy

Using machine learning classification algorithms, this paper reveals varying motives for postsecondary institutions adopting the test-optional admissions policy.

Everyone Wants to Win: Even the Admissions Officers

Winner of the 2019 Rhodes College Lynn Nettleton Prize in Economics, this paper uses fixed-effects regression models to study the symbiotic relationship of collegiate athletics and institutional research.

Using NCAA Track Data as a Predictor for Race Times

NCAA Track & Field results can be mined to create an ecosystem of robust running data.


Picks and algorithms


MLB Picks and Predictions

The page serves as a hub for my MLB picks and predictions.

NBA Picks and Predictions

Public NBA model coming soon!