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Pierre Pessarossi has a strong background in data science, with their most recent position as Lead Data Scientist at Back Market starting in 2022. Prior to that, they served as Lead Data Scientist at Younited Credit from 2017 to 2022. During their time at Younited Credit, Pierre managed the data science team and oversaw projects in various business domains, such as risk, fraud, recovery, granting, and marketing. Pierre successfully built a team of full stack data scientists, developed a scalable data science product for multiple countries and partners, and improved model development speed. Pierre also collaborated with the business, compliance, and data science teams of partner companies to build models based on their specific challenges. Before joining Younited Credit, they worked as a Data Scientist at Banque de France from 2013 to 2017. Overall, Pierre is experienced in the technical aspects of data science, including programming languages, libraries, and production tools.

Pierre Pessarossi has an extensive education history. From 2010 to 2013, they attended the University of Strasbourg, where they obtained a Doctor of Philosophy (PhD) in Economics. Prior to that, from 2005 to 2010, they pursued a Master's degree in Finance at Sciences Po Strasbourg. During their studies, they also spent the academic year 2007-2008 as a visiting student at Royal Holloway, University of London, focusing on the Economics department and European studies department.

In addition to their formal education, Pierre has obtained various certifications in the field of data science and natural language processing. These certifications include "Natural Language Processing with Attention Models" from Coursera (obtained in December 2021), "General and Python Data Science, and SQL (Hard)" from TestDome (obtained in September 2021), "Natural Language Processing with Sequence Models" from Coursera (obtained in August 2021), "Natural Language Processing with Classification and Vector Spaces" from Coursera (obtained in June 2021), "Natural Language Processing with Probabilistic Models" from Coursera (obtained in June 2021), "Convolutional Neural Networks" from Coursera (obtained in February 2018), "Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization" from Coursera (obtained in January 2018), "Structuring Machine Learning Projects" from Coursera (obtained in January 2018), "Neural Networks and Deep Learning" from Coursera (obtained in December 2017), and "Data Manipulation at Scale: Systems and Algorithms" from Coursera (obtained in February 2017).