Stéphanie Schaer, general engineer of Mines, has been, since September 2022, the interministerial director of digital (DINUM).

A former student of École Polytechnique (1997), she is also a graduate of the École nationale supérieure des telecommunications/Télécom Paris.

Her professional career is notably marked by stints at the Central Directorate for Information Systems Security (DCSSI, now ANSSI) from 2002 to 2006 then at the Ministry of the Economy, Industry and Employment where she is project manager on embedded electronics then head of the software industry office of the Directorate General for Competitiveness, Industry and Services in 2008.

She later became deputy regional director of businesses, competition, consumption, work and employment (Direccte) of Burgundy, then of Bourgogne-Franche-Comté. At the same time, in 2015, as an intrapreneur, she launched the State Startup "Signaux Faibles", which makes it possible to detect companies in difficulty early on, to better support them, using data held by administrations. This service, now deployed throughout France, has benefited from DINUM support programs: entrepreneurs of general interest (EIG) and the State Startup incubation program, Beta.gouv.

In 2019, Stéphanie Schaer became deputy director of Élisabeth Borne's cabinet, at the Ministry of Ecological and Inclusive Transition then at the Ministry of Labor where she would then be appointed head of the cabinet. When Élisabeth Borne is appointed to Matignon in May 2022, Stéphanie Schaer became advisor to the Prime Minister.

On September 26, 2022, she was appointed head of the interministerial digital department.

Arthur Schiltz is a consultant within the Technology Consulting department at PwC. Arthur joined PwC Belgium after obtaining a degree in Business Administration, with a major in Finance and a minor in Econometrics. Through his professional work on the SEMIC project he has garnered experience as a semantic developer, focusing on modelling and maintenance of the various SEMIC specifications. Among his topics of focus is interoperability for AI, where Arthur has worked on data models specifically designed for improving the interoperability of Machine Learning data.