I am a Lead Data Scientist at FleetOps, a company that leverages data and technology to improve the efficiency and transparency of the freight industry. With over 16 years of experience in data science, machine learning, and econometrics, I am passionate about applying my skills and knowledge to solve complex and impactful problems in various domains. At FleetOps, I design, manage, and implement data-driven solutions that address the asymmetry of data access in the freight industry. Using the wealth of data available through FleetOps deep integrations with ELD partners, I build quantitative tools for brokerages and carriers that streamline coverage, tracking, delivery, and payment processes. I also lead the Data Science cross-functional team to ensure that our solutions are aligned with the needs and goals of our customers and stakeholders. In addition, I have a strong academic background and a track record of publications and projects in machine learning, econometrics, and causal inference. I hold a PhD in Business Administration from the University of Brasília, a Master's degree in Statistics and Probability from the Universidade Federal de Minas Gerais, and a Bachelor's degree in Statistics from the University of Brasília. I have also completed postdoctoral fellowships in Machine Learning and Time Series Forecast at IME-USP and Machine Learning and Bayesian Inference at the University of Florida. I am an Adjunct Professor at Bellevue College, where I teach and research statistics and mathematics applied to business and economics.