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Loris Michel is a Data Scientist at QuantCo in Zürich, with a background in statistics, applied mathematics, and biostatistics. He has previously worked at ETH Zürich, Effixis, Nestlé, and the Swiss Federal Institute of Technology in Lausanne.
Title at QuantCo
Loris Michel is currently employed at QuantCo as a Data Scientist // Quant in Zürich. His role involves utilizing advanced quantitative methodologies and data analysis techniques to solve complex problems.
Education and Expertise
Loris Michel completed his education at prominent institutions. He earned a Doctor of Sciences (Dr. sc. ETH Zurich) in Statistics from ETH Zürich, studying from 2017 to 2021. Prior to that, he obtained a Master of Science (MSc) in Applied Mathematics with a concentration in Statistics and Probability from EPFL, from 2015 to 2017. He also holds a Bachelor of Science (BSc) in Mathematics from EPFL, completed between 2012 and 2015. Earlier, he graduated with a Maturité in Physics and Applied Mathematics from Gymnase de Chamblandes, from 2009 to 2012.
Professional Background in Quantitative Analysis
Loris Michel has a well-rounded background in quantitative analysis and data science. From 2017 to 2021, he served as a Graduate Research and Teaching Assistant at ETH Zürich. Concurrently, he co-founded Effixis, where he worked as a Quantitative Consultant from 2017 to 2021. His early career also includes a six-month internship in Biostatistics at Nestlé, focusing on statistical analysis of exploratory cohort studies. Additionally, he worked as a Teaching Assistant at the Swiss Federal Institute of Technology in Lausanne from 2013 to 2017.
Experience in Biostatistics and Clinical Trials
Loris Michel has specific experience in biostatistics and clinical trials, having worked at the Nestlé Research Center. His role there included statistical analysis of exploratory cohort studies and clinical trials, highlighting his expertise in biostatistics within health and nutrition research.
Specializations in Data Mining and Web Applications
Loris Michel specializes in data mining, particularly with applications in mobile health. He has experience in designing web applications, leveraging advanced methodologies and algorithms to extract valuable insights from data. His work is characterized by a strong interest in state-of-the-art data analysis tools and techniques.
