1. Provide AI / ML based « intelligent services » capabilities for ISO to embed into our existing IT solutions used throughout the lifecycle of standards : elicitation, development, management, publishing, and distribution
2. Create an automatic expert or advisor that exploits our organisational knowledge (processes, directives, rules of procedure, resolutions, MOUs, etc.). Improve relevance of information retrieval via semantic-aware search and/or conversational agents
3. Evolve our NLP-based text analysis technologies to better exploit the content from existing published standards or those being drafted online
4. Support and advise ISO/CS Business Units around advanced Data Science (coordinated with the Data Scientist) involving trained models for predictive analysis, etc.
5. In collaboration with the Data Engineer, improve data quality by implementing processes and tooling that better enforce the governance and policies that we are currently setting up
6. Form opinions (design etc.) and clearly communicate / advocate for them
Key responsibilities
Hands-on (design and implementation):
7. Architect and build a central platform & APIs for “intelligent services” to expose consolidated endpoints for ISO applications to use
8. Leverage our hybrid architecture for cloud hosted competencies vs on-premises performant delivery
9. Implement MLOPS best practices to manage models and technical/systems debt
Foresight (research):
10. Highlighting emerging technologies that could offer solutions to new classes of problems
11. Advising on industry trends and lessons learned. What parts of the hype from 12 months ago have delivered value in other organisations and how applicable is this to ISO?
Collaborations(Data platform, Business Intelligence, Development):
12. Business: Advocate designs and opinions to less-technical and non-technical users in both written documents and oral presentations
13. Data platform: Use Azure Databricks/MLFlow for data cleaning, model training & serving
14. BI: provider of datasets or leveraging the existing platform for data visualizations or analysis
15. Development: liaise with IT engineering to define and use AI / ML capabilities in our existing and future apps
Report to: Headof Data
Qualification and Experience
16. Universitydegree in Information Technology or Data Science
17. Candidatesmust have worked on several IT implementation projects in the field of AI/ML.Ideally a few years of corporate environment
Skills
18. Excellentcommunication and interpersonal skills
19. Proficiencyin English; French is also often used in the IT department
20. Adheres to ISO's core values of Respect, Integrity, Collaboration, Growth Mindset, and Pushing Boundaries