Gabriel Yawin

Gabriel Yawin

Quantitative Analyst @ AXA XL

About Gabriel Yawin

Gabriel Yawin is a Quantitative Analyst currently working at AXA XL in Stamford, Connecticut. He has a background in Mathematics and Political Science, with experience in data science, deep learning, and data storytelling.

Work at AXA XL

Gabriel Yawin has been employed as a Quantitative Analyst at AXA XL since 2020. This role is based in Stamford, Connecticut, and involves applying quantitative methods to support decision-making processes within the organization. His work focuses on analyzing complex data sets to derive insights that inform business strategies.

Previous Experience at Luxottica

Prior to his current position, Gabriel worked at Luxottica as an Apprentice Optician from 2016 to 2020. During this four-year tenure in Connecticut, he gained practical experience in the optical industry, contributing to customer service and product knowledge.

Data Science Fellowship at Springboard

Gabriel served as a Data Science Fellow at Springboard for seven months in 2020. This experience allowed him to deepen his understanding of data science principles and practices, further enhancing his analytical skills and preparing him for his role at AXA XL.

Education and Expertise

Gabriel Yawin holds a Bachelor of Arts in Mathematics and Political Science from Central Connecticut State University, which he completed from 2016 to 2019. He also achieved a Data Science - Machine Learning Specialization from Springboard in 2020. His educational background equips him with a strong foundation in quantitative analysis and data science.

Skills in Data Science and Analysis

Gabriel possesses advanced skills in deep learning, particularly with TensorFlow and Keras. He is experienced in using Spark and PySpark for large-scale data processing and analysis. Additionally, he specializes in automation and UI creation, which enhances data analysis processes. His ability to utilize data storytelling allows him to translate complex data insights into meaningful narratives.

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