Michaël Ullah

Michaël Ullah has extensive work experience in data analysis and data science roles. Michaël is currently working at TOTEM as a Data Lead, where they focus on the challenges faced by real estate professionals and HR departments in terms of attractiveness and quality of life in the workplace. Prior to that, they worked as a Data Scientist at Foxintelligence, where they conducted a data science mission as part of their master's program. At Myos, they served as a Data Scientist and developed a risk model for loans based on forecasting product sales on Amazon. Michaël also worked as a Big Data Analyst at Groupe Renault, where they built a solution for reporting the CO2 emissions of the worldwide supply chain. Additionally, they have experience as an Industrial Planning Consultant at GE, a Data Analyst at METRO PROPERTIES, and in lean manufacturing at the MÄDER GROUP.

Michaël Ullah completed their education in a chronological order. Michaël began by attending Lycée Janson-de-Sailly from 2012 to 2015, where they pursued a degree course preparing for the competitive entrance examination for the French Schools of Engineering with a focus on Maths and Physics. Following this, from 2015 to 2018, they attended IMT Atlantique and obtained a Master's degree in Engineering, specializing in Algorithmes d'optimisation et Recherche Opérationnelle.

In 2017, Michaël Ullah had the opportunity to study at Technische Universität Berlin for a brief period through the Erasmus program, focusing on Wirtschaftsingenieurswesen (Economics & Supply Chain Analytics). Subsequently, they attended ESSEC | CentraleSupélec from 2019 to 2020, where they pursued a Master of Science (MS) degree in Data Sciences & Business Analytics.

In addition to their formal education, Michaël Ullah also obtained several certifications. In January 2019, they earned a TOEIC score of 990/990 through the TOEIC® Program. Michaël also completed several Coursera courses, including "Negociation Fundamentals" in October 2019, "Serverless Machine Learning with Tensorflow on Google Cloud Platform" in May 2019, and "Google Cloud Platform Big Data and Machine Learning Fundamentals" in April 2019.