Cormac Dillon
About Cormac Dillon
Cormac Dillon is a Data Scientist at First Derivatives, where he has worked since 2017. He has experience in equity risk data and has collaborated with a Tier 1 investment bank in both New York and Budapest.
Work at First Derivatives
Cormac Dillon has been employed at First Derivatives since 2017, where he holds the position of Data Scientist. Over the course of seven years, he has contributed to various projects and initiatives within the company, leveraging his expertise in data science to support client needs. His role involves working with complex data systems and providing insights that help drive decision-making processes.
Experience with Investment Banks
Cormac Dillon has gained valuable experience working with a Tier 1 investment bank client. His work has taken him to major financial hubs, including New York and Budapest, where he has applied his data science skills in high-pressure environments. This experience has enhanced his understanding of the financial sector and the specific data challenges faced by investment banks.
Education in Physics
Cormac Dillon studied at the National University of Ireland, Galway, where he earned a Bachelor of Science degree in Physics. His studies spanned from 2013 to 2017, providing him with a solid foundation in analytical thinking and problem-solving skills that are essential in the field of data science.
Technical Skills and Proficiencies
Cormac Dillon possesses a range of technical skills relevant to data science. He is proficient in Kdb+/q scripting and development, and he has experience with SQL and Sybase databases. Additionally, he is skilled in bash/shell scripting and version control systems such as git and perforce. He also has basic knowledge of Python, which complements his data analysis capabilities.
Experience with Equity Risk Data
During his tenure at First Derivatives, Cormac Dillon worked with equity risk data and maintained a complex tick architecture. This role required attention to detail and a strong understanding of financial data structures, allowing him to effectively manage and analyze data critical to investment strategies.