Data/ML Engineer

Data/ML Engineer  Be part of building the data foundation for the key commercial strategic AI use cases, then take ownership of the MLOps infrastructure that gets our models into production. This is a chance to set the technical standard for the data and ML infrastructure at Lundbeck.  Your new role   You'll join our newly established data, insights and AI team in GCX. In your first phase, the priority is data engineering: building ingestion and integration across fragmented commercial data sources, standardizing definitions, and creating the shared data foundation the rest of the team builds on. As models move from prototype to production, your focus expands into MLOps: pipelines, deployment, monitoring and reliability for the models.  Your responsibilities will include  Data engineering (near term focus)  Building and maintaining data pipelines that ingest and integrate data from systems such as Veeva, Marketing Cloud, Snowflake and other commercial systems Designing a shared taxonomy and data model across fragmented, non standardized sources so the team is working from a common foundation Ensuring data quality, consistency and reliability for analytics, ML and GenAI use cases Partnering with Data Scientist(s) and GenAI Engineer to unblock their work with clean, well structured, accessible data Partnering with BI so descriptive reporting and predictive pipelines draw from the same reliable foundation rather than duplicating effort  MLOps (growing focus as the team's models mature)  Building CI/CD pipelines for model deployment Implementing experiment tracking and model registries (e.g. MLflow) Setting up model monitoring for performance, drift and reliability in production Supporting containerization and deployment via Docker and Kubernetes or cloud platforms Establishing best practice for how models move from prototype to reliable production across the team  Platform and infrastructure  Managing cloud infrastructure (Azure and/or AWS) supporting the team's data and ML workloads Applying infrastructure as code (preferably Terraform) for reproducible, version controlled environments Implementing security, access control and secure coding practices across the data and ML stack Automating operational tasks and maintaining Linux based environments  Your future team You'll join GCX's newly established data, insights and AI team, responsible for the commercial intelligence layer: building competitively differentiating predictive intelligence loops. We stay close to the business to make sure what we build actually gets used, in service of reaching millions of people living with serious chronic diseases. The team is young enough that you'll help shape its culture and ways of working. This is a build from scratch opportunity, not a seat on an established team, and this role in particular lays the foundation everyone else builds on.  What you…