Resume
Basics
| Name | Matthew D. Baird |
| Title | Senior Staff Economist |
| Employer | |
| matthewdbaird@gmail.com | |
| Phone | +1 (412) 660-1457 |
| Url | mdbaird.github.io |
| Summary | Senior Staff Economist and applied data scientist with deep expertise in causal inference, experimentation, and large-scale behavioral data. I lead end-to-end research at LinkedIn—spanning statistical modeling, labor economics, and experimentation—to inform policy, product, and business decisions on workforce dynamics, AI adoption, and economic opportunity. I have a Ph.D. in economics from the University of California, Los Angeles (UCLA). |
| Highlights |
|
Work Experience
-
2022.07 - present LinkedIn Senior Staff Economist
Leads applied research on labor-market behavior using large-scale platform data. Using advanced statistical methods in Python, R, and SQL, I design and analyze experiments and quasi-experimental studies evaluating policy changes, AI adoption, and product-relevant labor outcomes. I direct the Economic Opportunity research program and serve as a technical leader across the research and data science community. I regularly partner with policy, product, and legal teams, translating analysis into decisions affecting millions of users.
-
2013.04 - 2023.12 RAND Corporation Adjunct Economist • Full Economist • Associate Economist
Conducted applied research on labor economics, social policy, and causal inference methods. Led end-to-end research projects, including study design, data collection and management, statistical modeling, and dissemination of results to technical and non-technical audiences. Collaborated with multidisciplinary teams of economists, statisticians, and policy experts to inform public policy and program evaluation.
-
2018.10 - 2022.06 RAND Center for Causal Inference Co-Director
Directed the RAND Center for Causal Inference, overseeing research initiatives and collaborations focused on advancing causal inference methods and their applications in social science research. Facilitated workshops, seminars, and training sessions to promote best practices in causal inference among researchers and practitioners.
-
2018.09 - 2022.06 Pardee RAND Graduate School Professor of Policy Analysis
Taught doctoral-level courses on causal inference and applied econometrics, mentoring students in research design and analysis. Supervised dissertations and provided guidance on methodological approaches to complex policy issues.
-
2010.01 - 2016.12 Carnegie Mellon University • University of Pittsburgh • University of California, Los Angeles • Brigham Young University Part-Time Instructor (Economics)
Taught courses on applied econometrics, labor economics, and public policy (primarily doctoral-level), focusing on the intersection of economics and policy analysis.
Education
Skills
Methods & Analytics
- Causal inference
- A/B testing & experimental design
- Quasi-experimental methods
- Statistical modeling
- Quantitative research
- Data visualization
- Predictive modeling (e.g., random forests)
Applied Economics & Policy
- Applied econometrics
- Labor economics
- Program evaluation
- Education policy
- Distributional analysis & equity
- Generative AI & technology impacts
Programming
- R
- Python
- SQL
- Git
- Scala, PySpark (working knowledge)
- Airflow (working knowledge)
- Stata
- Matlab
Leadership & Communication
- Technical leadership
- Research design
- Technical writing
- Teaching & mentorship
- Executive & stakeholder communication