Nicolas is an Empirical Economist with a strong set of skills in programming. Most proficient in STATA, Python, R and GAMS which enables him to apply his knowledge of experimental, quasi-experimental, machine learning, and macrosimulation methodologies. He has proven to be able to build his own datasets using web scrapers, predict with high accuracy the likelihood of microcredit defaults, expand CGEM models to contain components of MAMS models, run quasi-experimental models and RCT research designs, and work on large panel studies. He also has 3 years of experience at the Ministry of Finance and at the Department of Economic Development of Indigenous Affairs at the Executive Council of the Government of Quebec which makes him a well-rounded and versatile economist. He has conducted his own field research in South Korea thanks to a collaboration between his home university and the Korean Institute of Health and Social Affairs in Sejong. And he has coauthored on a large RCT conducted by Harvard and MIT that became the reference on evaluating the efficacy of Nurse-Home Visiting in the United States.