David Mammarella

David Mammarella has a diverse work experience spanning different roles and industries. David is currently working as a Data Analyst at theScore since 2022. Prior to this, they served as a Data Analyst at The Alcohol and Gaming Commission of Ontario from 2021 to 2022. David also worked as a Data Architect at Athlete Technology Group from 2021 to 2022.

In terms of their academic background, David was a Mathematical Researcher at the University of Guelph from 2018 to 2020. During this time, they conducted research in mathematics, specifically focusing on quantum error correction using functional analysis, operator and linear algebra. David also worked as a Graduate Research and Teaching Assistant at the university during the same period.

Before joining the University of Guelph, David worked as a Data Analyst at Customer Marketing Group, Inc. in 2018, where they gained experience in analyzing data. David also worked as a Teaching Assistant and Tutor at the University of Windsor from 2016 to 2018, and as a Lifeguard/Swim Instructor at the City of Windsor from 2014 to 2018.

Overall, David's work experience showcases their expertise in data analysis, research, and teaching, with a focus on mathematics and quantum information.

David Mammarella has a Bachelor's degree in Mathematics from the University of Windsor, which they obtained between the years 2013 and 2018. David then pursued a Master's degree in Mathematics at the University of Guelph from 2018 to 2020. Currently, they are enrolled at McGill University, where they are set to complete a Professional Development Certification in Data Science and Machine Learning between 2021 and 2023.

In addition to their formal education, David has obtained several certifications. In 2020, they completed the certificates "Data Engineering for Everyone" and "Introduction to Data Engineering" from DataCamp. David also obtained the "Introduction to TensorFlow in Python" certification from DataCamp, and completed various courses from IBM, including "Applied Data Science Capstone," "Data Analysis with Python," "Data Visualization with Python," "Databases and SQL for Data Science," "Machine Learning with Python," and "Python for Data Science and AI."

Furthermore, in 2021, David acquired the "NLP with Python for Machine Learning Essential Training" certification from LinkedIn. In 2020, they completed the certifications "Neural Networks and Deep Learning" and "Structuring Machine Learning Projects" from deeplearning.ai. Lastly, it is worth noting that David began "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization" but did not provide specific completion details.