Yacine Lapointe works in the preparation and analysis of wearables data, consumer transactions data, and geospatial mobility data. She holds a B.A. and M.A. in Economics from Université Laval in Quebec City, where her research focused on labour and behavioural economics, particularly on policies promoting workforce prosperity.
Her previous work experience includes serving as a Graduate Research Assistant in the Department of Economics at Université Laval and completing an internship at the Treasury Board of Canada Secretariat. Throughout her academic and professional career, she has developed substantial experience in optimization techniques, parametric and non-parametric estimation methods, and simulations for empirical economic research. Yacine is proficient in R and Python programming languages, Latex, and is actively expanding her skills in Markdown and Github.
Her previous work experience includes serving as a Graduate Research Assistant in the Department of Economics at Université Laval and completing an internship at the Treasury Board of Canada Secretariat. Throughout her academic and professional career, she has developed substantial experience in optimization techniques, parametric and non-parametric estimation methods, and simulations for empirical economic research. Yacine is proficient in R and Python programming languages, Latex, and is actively expanding her skills in Markdown and Github.