Mario Javier Carrillo
About Mario Javier Carrillo
Mario Javier Carrillo is a Senior Data Scientist at Cision and an Adjunct Faculty member at the University of San Francisco, with extensive experience in data science and research roles across various organizations.
Current Role at Cision
Mario Javier Carrillo currently holds the position of Senior Data Scientist at Cision, based in the San Francisco Bay Area. In this role, he is responsible for applying his expertise in data science to develop and implement advanced data analytics solutions. His work involves producing and delivering data briefs to senior managers and other stakeholders.
Prior Experience at Compassion International
From 2019 to 2022, Mario Javier Carrillo was a Senior Data Scientist at Compassion International, also located in the San Francisco Bay Area. During his tenure, he worked on various data-driven projects aimed at improving organizational outcomes and providing valuable insights to stakeholders.
Academic Roles at University of San Francisco
Mario Javier Carrillo is an Adjunct Faculty member at the University of San Francisco, specializing in Machine Learning. In this academic role, he teaches courses and guides students in understanding complex machine learning concepts and their real-world applications.
Educational Background in Data Science and Economics
Mario Javier Carrillo has a comprehensive academic background. He holds a Master's degree in International Development Economics from the University of San Francisco, which he completed from 2011 to 2013. Additionally, he earned a Certificate in Data Science from General Assembly in 2016 and a Certificate in Machine Learning Engineering from FourthBrain in 2021. His earlier studies include a year of Mathematics and Economics at the University of Minnesota-Twin Cities and a TOEFL Certificate from Westchester Community College.
Technical Skills and Self-Development
Mario Javier Carrillo is proficient in various technical skills, including LaTex and Python, which he learned independently. He has a proven track record in research and survey design, causal analysis, and machine learning prediction. His ability to quickly acquire new software skills further underscores his commitment to professional growth and adaptability.