Miguel Lanza is an applied economist with a decade of experience at institutions shaping housing finance and global development, currently serving as an Economist at Fannie Mae after roles at Freddie Mac, the IMF, and the World Bank. Trained at Georgetown (MA in Applied Economics) with a machine learning certificate from LSE, he blends rigorous empirical analysis with practical policy and credit-risk applications. He has hands-on exposure to credit risk transfer, open government data, and development economics, and thrives under tight deadlines and constrained budgets. Known as a fast learner and collaborative problem-solver, he often translates complex analytical insights into feasible, implementation-ready solutions for stakeholders across public and private sectors.
10 years of coding experience
Master's degree, Applied Economics, Master's degree, Applied Economics at Georgetown University
London School of Economics and Political Science
Bachelor's degree, Economics, Bachelor's degree, Economics at Universidad Privada de Santa Cruz de la Sierra
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