Hannah Carson

Hannah Carson has a diverse work experience spanning multiple roles. Hannah started their professional career in 2012 as a Summer Fellows Research Intern at Presbyterian College, where they analyzed thin film stress evolution and monitored whisker growth using scanning electron microscopy.

In 2013, Hannah worked as an REU Research Grant recipient at Texas A&M University, conducting an efficiency study for the new muon telescope detector at STAR. Hannah utilized the C++ based ROOT framework to analyze Monte Carlo simulated data.

Continuing their education, Hannah joined Presbyterian College again in 2013 as part of their capstone research, studying the morphology of tin whiskers during accelerated growth experiments. Hannah'sresponsibilities included chemical etching and analysis of tin whiskers with an electron microscope.

Moving on to the University of Arizona in 2014, Hannah served as a Graduate Research Assistant for the ATLAS collaboration of CERN. Hannah worked on analyzing proton-proton collisions in search of t-tbar resonance pairs, calculating data-driven scale factors, and developing techniques to improve statistical certainty and sensitivity of the analysis.

Hannah's work experience also includes positions at RSG - Resource Systems Group, Inc., where they held roles as an Analyst, Senior Analyst, and currently as a Consultant.

Throughout their career, Hannah has demonstrated a strong passion for data analysis, particularly in the field of high energy physics.

Hannah Carson has a strong academic background in physics. Hannah completed their Bachelor of Science degree in Physics from Presbyterian College in 2014. During their time at Presbyterian College, they also pursued a Bachelor of Arts degree in French Studies. In 2017, they obtained a Master of Science degree in Physics from the University of Arizona.

In addition to their formal education, Hannah Carson has obtained several certifications in various data science and analytics fields. In 2018, they acquired certifications in Big Data Foundations: Techniques and Concepts, Business Analytics Foundations: Predictive, Prescriptive, and Experimental Analytics, Data Science Foundations: Python Scientific Stack, Advanced SQL for Data Scientists, Excel: PivotTables for Beginners, Looker First Look, Machine Learning & AI Foundations: Value Estimations, Python for Data Science Essential Training, and SQL Essential Training. These certifications highlight their commitment and expertise in the field of data science and analytics.