The Informatics Experience initiative is a strategic program designed to address the fragmentation of content within our Informatics landscape. Currently, key information is scattered across numerous outdated and disconnected sources, hindering usability and efficiency. This initiative will centralise and standardise content, improve content governance, and enhance user journeys through the use of structured, composable content.
We are seeking a Senior Data Scientist with a strong background in observability, behavioural analytics, and AI integration. You will lead efforts to analyse user behaviour, support AI agent enablement, and help shape our observability pipeline from the ground up. This is a high-impact role that bridges data science, UX, software architecture, and enterprise AI.
responsibilities :
Define and execute observability strategy for user profiling with tailored metrics
Select and integrate appropriate data sources for user behaviour tracking
Design and deploy monitoring solutions in live, complex environments using Grafana and OpenTelemetry
Lead architectural design and implementation of Enterprise Search (e.g., Sinequa) and related technologies
Apply behavioural modelling to create actionable insights and predictive models
Facilitate collaboration between traditional data science and AI agent teams
Build dashboards and data visualisations tailored for technical and non-technical stakeholders
Contribute to the definition of data governance principles, data lifecycle, and security protocols for AI-driven systems
requirements-expected :
Proven experience in observability strategy creation and execution
Expertise with Grafana and Enterprise Search (preferably Sinequa)
Practical knowledge of OpenTelemetry, log/metric/trace collection
Experience with E2E observability deployment in multi-system environments
Strong experience in user behaviour modelling and segmentation
Familiarity with AI agent architectures in enterprise settings
Ability to evaluate and optimise model performance
Understanding of the role of AI tools in user profiling
Practical use of FAIR principles in data management
Knowledge of GDPR and secure handling of personal data
Experience with data stewardship processes and lifecycle definition
Understanding of AI-specific data security implications
Strong data storytelling and visualisation skills
Ability to communicate complex concepts to technical and business audiences
Experience in cross-functional, international teams
Ability to act as a technical liaison between data science and AI engineering streams
