Artificial Intelligence Facilitator
De Wiki Campus Cyber
== What is the role of the AI facilitator? The role of the AI facilitator is to bring together cybersecurity teams and data scientists:
- Leading the cross-functional cyber and data science community (AI for and through cyber);
- Identify ML opportunities and benefits for cyber teams in their activities (cyber and non-cyber);
- Raise awareness of cyber issues among data scientists, and even facilitate access to or generation of cyber data;
- Promote the implementation of IA Security champions on the operational side and provide them with intelligence.
== His day-to-day activities Working directly with the CISO, you will be responsible for facilitating exchanges, interaction and collaboration with the community of data scientists. His or her cross-disciplinary knowledge of cybersecurity and interpersonal skills will enable him or her to :
- Using a community of data scientists and cybersecurity teams to promote exchanges and news on cyber needs in the field
- Make an inventory of the skills required and the cyber security expectations of the data scientist community in order to make them operational (training, tools, contacts, etc.)
- Make cyber security teams aware of the specific issues/capabilities related to AI (attacks on companies' AI or possible uses of AI on the cyber side);
- Facilitate the creation and implementation of cyber security measures to protect AI systems. Then promote their implementation.
- Contribute to the implementation of "cyber" business metrics for evaluating the performance of ML models;
- Relaying intelligence on incidents and public research papers - finding and promoting associated training - on attack techniques exploiting AI to AI sec champions and the community.
Expected skills
Organisational skills
- Maîtrise de l’organisation ;
- Maîtrise des processus de l’Entreprise ;
- Capacités d’analyse des difficultés Cyber et à quantifier leurs impacts, construire le budget du projet ;
- Savoir communiquer avec le métier cyber à de multiples niveaux (Opérations / Management / Stratégie / Budget / RSSI)
Compétences data science
- Compréhension des données utiles à la cyber sécurité
- Manipulation et transformation des données
- Connaissances ML pratiques (Développement et intégration ML)
Compétences cybersécurité
- Etre professionnel de la cybersécurité
- Avoir des compétences dans le domaine de la sécurisation de la donnée
- Sécurisation des pipelines data
