Alessandro Pagliero, PhD

Alessandro Pagliero, PhD

Lead Machine Learning Engineer @ ThoughtWorks

About Alessandro Pagliero, PhD

Alessandro Pagliero, PhD, is a Lead Machine Learning Engineer with extensive experience in both academic and industry settings. His career spans various roles in data engineering, business analytics, and machine learning, supported by a strong educational background in physics and material sciences.

Current Role as Lead Machine Learning Engineer

Alessandro Pagliero serves as the Lead Machine Learning Engineer at ThoughtWorks, a position he has held since 2024. In this role, he focuses on developing and implementing machine learning solutions that address complex business challenges. His expertise in data-driven methodologies allows him to lead projects that leverage advanced analytics and machine learning techniques.

Experience at ThoughtWorks

Prior to his current role, Alessandro worked at ThoughtWorks as a Senior Machine Learning Engineer from 2021 to 2023. During this time, he contributed to various projects that integrated machine learning into business processes. His experience at ThoughtWorks reflects a commitment to innovation in technology and analytics.

Career Background in Data Engineering and Analytics

Alessandro has a diverse career history that includes roles in data engineering and analytics. He worked at XITE as a Data Engineer from 2017 to 2019 and later as a Machine Learning Engineer from 2019 to 2021. Additionally, he served as a Business Intelligence Analyst at TIP Trailer Services from 2016 to 2017. This combination of roles has equipped him with a comprehensive understanding of data systems and analytics.

Educational Background in Physics and Engineering

Alessandro holds multiple degrees from Università degli Studi di Torino. He earned a Bachelor's degree in Physics (1997-2006) and a Master's degree in Physics of Advanced Technologies (2007-2011). He also completed a PhD in Chemical and Material Sciences at the same institution from 2012 to 2015. His educational background provides a strong foundation for his work in machine learning and data science.

Transition from Academia to Industry

Alessandro transitioned from a research career in solid state physics to various roles in industry, including business analytics, data engineering, and machine learning engineering. His experience as a Post-doctoral Research Fellow at Stockholm University from 2015 to 2016 further enriched his understanding of data-driven problem solving, bridging the gap between academic research and practical applications.

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