Gabe Smith
About Gabe Smith
Gabe Smith is a Senior Machine Learning Success Manager at Snorkel AI, where he has worked since 2024. He has a background in data science and analytics, with previous roles at McKinsey & Company and various internships in the field.
Current Role at Snorkel AI
Gabe Smith currently serves as a Senior Machine Learning Success Manager at Snorkel AI, a position he has held since 2024. In this role, he focuses on enhancing the success of machine learning initiatives within the organization. His responsibilities include collaborating with clients to ensure effective implementation of machine learning solutions, providing strategic guidance, and optimizing processes to improve outcomes.
Previous Experience at Snorkel AI
Prior to his current role, Gabe worked at Snorkel AI as a Machine Learning Success Manager from 2023 to 2024. During this year, he contributed to the development and execution of machine learning strategies, assisting clients in navigating the complexities of machine learning applications and ensuring successful project outcomes.
Professional Background in Consulting
Gabe has significant experience in consulting, having worked at McKinsey & Company as an Analyst in Risk Dynamics from 2021 to 2023. His role involved analyzing data to assess risks and provide insights to clients. He also served as a Summer Analytics Fellow at McKinsey in 2019, where he gained foundational experience in analytics and consulting practices.
Educational Qualifications
Gabe holds a Master of Science in Computer Science with an emphasis on Machine Learning and Artificial Intelligence from Brigham Young University, which he completed from 2020 to 2021. He also earned a Bachelor of Science in Applied and Computational Mathematics, with concentrations in Economics and Machine Learning, from the same institution between 2016 and 2020. His educational background supports his expertise in statistical modeling and machine learning.
Skills and Areas of Focus
Gabe possesses a strong focus on the intersection of data, modeling, and strategy. He emphasizes enhancing organizational productivity, efficiency, and profitability through the application of statistical modeling and machine learning. His passion for technological advancement drives his belief in utilizing data to develop effective business solutions.