Lyndsay Old, Ph.D
About Lyndsay Old, Ph.D
Lyndsay Old, Ph.D., is a Senior Data Scientist at Cabify with a background in physics and extensive experience in data science and research.
Current Title at Cabify
Lyndsay Old, Ph.D., is currently a Senior Data Scientist at Cabify. She started her role at the company in 2024 and is based in Madrid, Community of Madrid, Spain. Her work focuses on applying advanced data science techniques to enhance the company's operational efficiency and customer experience.
Previous Role at DAZN Group
Before joining Cabify, Lyndsay Old worked as a Senior Data Scientist at DAZN Group from 2021 to 2023. In this role, she applied machine learning and data analysis skills to deliver data-driven solutions, enhancing customer experience and optimizing business performance for the global sports streaming platform.
Research Fellow at European Space Agency
Lyndsay Old served as a Research Fellow at the European Space Agency (ESA) from 2018 to 2021 in the Madrid Area, Spain. During her tenure, she conducted cutting-edge research, developing expertise in statistical modeling and data visualization. Her work at ESA contributed significantly to scientific advancements in space research.
Postdoctoral Research at University of Toronto
From 2015 to 2018, Lyndsay Old was a Postdoctoral Research Fellow at the University of Toronto. This position helped her hone her research skills in data science, focusing on statistical modeling and machine learning. Her work at the university led to various scientific contributions and publications.
Educational Background
Lyndsay Old obtained her Doctor of Philosophy (Ph.D.) in Physics from the University of Nottingham, studying from 2011 to 2015. She also holds a Bachelor of Science (B.S.) in Physics and Astronomy from the University of Glasgow, completed between 2007 and 2011. Her education provided a strong foundation for her career in data science.
Technical Skills and Certifications
Throughout her career, Lyndsay Old has acquired multiple certifications in machine learning and data science. Her technical skills include proficiency in Python, SQL, various ML libraries, AWS, and Azure. These skills have enabled her to develop innovative solutions to complex science and business challenges across diverse domains.