Catherine Boothman has a diverse work experience spanning various industries and roles. Currently, they are working as a Software Developer & Data Scientist at SiriusXT. Prior to this, Catherine worked at Citi as a Data Scientist, where they developed POC projects within the Citi Innovation Lab, focusing on fraud detection models, alternative credit scoring models, graph analytics, trade risk assessment, and client user experience enhancement. Catherine also handled industry grant applications and participated in workshops to showcase the Innovation Lab's data science capabilities.
Before joining Citi, Catherine served as a Data Scientist at Amdocs, where they worked on Data Science as a Service projects for major Telecoms companies. Catherine utilized customer journey analytics and developed models using R, Python, and Java. Catherine also worked with big data sets stored in HDFS and employed Hive and MapReduce for data exploration and engineering. Additionally, Catherine focused on algorithm and analytics logic development through proof of concept projects using Spark and Spark Streaming.
Prior to Amdocs, Catherine was a Data Analytics & Software Developer at Openet, where they applied real-time data analytics on stream data using R and Python models. Catherine deployed visual solutions in a Java application using elements of the "Lambda Architecture" concept for real-time Big Data processing. Catherine also developed models in R and used the predictive model markup language to make the application independent of R.
Furthermore, Catherine gained practical work experience in the IT industry through a six-month work placement as part of their student role in the DT265 HDip in Computing Conversion Course at the Dublin Institute of Technology, School of Computing.
Additionally, Catherine worked as a Research & Development Engineer at Innalabs, where they analyzed and modeled gyro sensor output data using Octave/MATLAB scripting. Catherine also managed the installation of new manufacturing equipment and relocated R&D equipment from a facility in Kiev to a new location in Dublin.
Catherine's previous role as a Software Developer at NewLambda Technologies involved developing user software for a newly designed EUV light source tool using Microsoft Visual Basic language. Catherine communicated with the product through National Instrument GPIB cards and RS232 ports.
Catherine also has experience as a Meteorological Officer focused on software development at Met Eireann, where they developed a software program to monitor the Earth's magnetic field variations and create data files for international organizations. Catherine's responsibilities included the care and maintenance of meteorological instrumentation and communication facilities.
Catherine began their career as a Researcher at Dublin City University, where they programmed a motorized x-y stage and conducted characterizations of new sol-gel materials for medical diagnostic waveguide sensors and microfluidic channels.
Lastly, Catherine completed their PhD in CRANN, during which they produced reliable and publishable data of scientific interest. Catherine worked with highly specialized equipment and participated in outreach activities to promote scientific research.
Catherine Boothman's education history includes a HDip in Computing from Technological University Dublin, which they completed from 2013 to 2014. Prior to that, they obtained a Doctor of Philosophy (PhD) in Condensed Matter and Materials Physics from Trinity College Dublin, where they studied from 2004 to 2009. Their undergraduate degree, a Bachelor of Science (BSc) in Applied Physics, was earned at Dublin City University from 1999 to 2003.
In addition to their formal education, Catherine has also completed various certifications. These include "Introduction to Deep Learning & Neural Networks with Keras" from Coursera Course Certificates in October 2019, "Machine Learning With Big Data" from Coursera in January 2019, "Big Data Integration and Processing" from Coursera in December 2018, "Big Data Modeling and Management Systems" from Coursera in November 2018, and "Introduction to Big Data" from Coursera in November 2018.
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