ÂÜÀòÂÒÂ×

Patrick O'Connell has a diverse work experience in various roles and industries. Patrick worked as a Data Analyst at BCT Partners starting in 2022, where they built machine learning models for government, philanthropic, and nonprofit projects. Patrick extracted summaries and relevant topics from documents using GPT3 and used Sentence Similarity with Hugging Face language models to identify relevant documents.

Prior to that, Patrick worked as a Python/Data Science Instructor Associate at General Assembly from 2019 to 2022. Patrick taught Data Science to enterprise clients and completed a 12-week Data Science Intensive boot camp course.

From 2010 to 2019, Patrick held the position of Apps Dev Technical Specialist at Citi Group. Patrick researched automating KYC Adverse Media Screening using NLP and designed and implemented enterprise applications using SQL databases and web services.

Patrick started their career at Chubb in 2008 as a Senior Programmer Analyst. Patrick developed software solutions for insurance applications, including Predictive Modeling. Patrick proposed and implemented an automated integration test tool for Predictive Modeling, successfully executing 15,000 tests to ensure model validity.

Patrick O'Connell has a Master of Science (M.S.) degree in Computer Science from Rutgers University–New Brunswick. Prior to that, they obtained a Bachelor of Engineering (B.E.) degree in Mechanical Engineering from University College Dublin. In 2018-2019, they pursued a Data Science certification from General Assembly. Additionally, in May 2016, they earned a certificate in Stanford University Machine Learning from Coursera Course Certificates.