Valentina P.
About Valentina P.
Valentina P. is an Associate Big Data Engineer at Quantexa in London, England, where she has worked since 2022. She has collaborated with the UK Space Agency and the European Space Agency on a Methane Detection Intelligence System and has a background in physics and astrophysics from Queen Mary University of London.
Work at Quantexa
Valentina P. has been employed at Quantexa as an Associate Big Data Engineer since 2022. In this role, she has contributed to various projects, including a collaboration with the UK Space Agency (UKSA) and the European Space Agency (ESA) to develop a Methane Detection Intelligence System. Her work involves analyzing large datasets and applying data science techniques to derive insights. Valentina has adapted to remote work during the pandemic, showcasing her self-management skills and ability to work independently.
Education and Expertise
Valentina P. holds an MSci in Physics with Astrophysics from Queen Mary University of London, which she completed from 2017 to 2022. Additionally, she studied Classical and Ancient Studies at Sapienza Università di Roma, earning a Bachelor of Arts (BA). Her academic background provides her with a strong foundation in scientific principles and data analysis, which she applies in her current role in big data engineering.
Background
Before joining Quantexa, Valentina P. gained experience as an Undergraduate Student Researcher at Queen Mary University of London from 2019 to 2020. She also completed a Scientist Intern position at Recycle2Trade as part of the SEPnet Summer Placement in 2020. These roles allowed her to develop research skills and gain practical experience in data analysis and scientific methodologies.
Achievements in Data Science Communication
Valentina P. regularly presents complex data science work to non-technical teams, which has enhanced her communication skills. This ability to convey intricate concepts in an accessible manner is crucial in her role as a Big Data Engineer, where collaboration with diverse teams is often necessary. Additionally, she has conducted scientific research focused on image data destriping algorithms, further contributing to her expertise in data processing.