The Data Science – MLOps Engineer role collaborates with data scientists, analysts, and commercial operations to design, deploy, and manage machine learning systems that enhance sales effectiveness and engagement
Job Summary
The Data Science – MLOps Engineer role collaborates with data scientists, analysts, and commercial operations to design, deploy, and manage machine learning systems that enhance sales effectiveness and engagement.
This position is responsible for ensuring that models are reproducible, compliant, performant, and scalable throughout their lifecycle—from experimentation to production.
At AstraZeneca's Alexion division, we champion diversity and foster an energizing culture where new ideas thrive.
Matching Summary
The Data Science – MLOps Engineer role collaborates with data scientists, analysts, and commercial operations to design, deploy, and manage machine learning systems that enhance sales effectiveness and engagement.
Skills & Requirements
Must-have
Model Lifecycle Management
Data Pipeline Development
Production Operations
Monitoring & Observability
Model Governance & Compliance
Experiment Management
Release & Change Management
Security & Access Controls
Cost Optimization
Collaboration & Enablement
Documentation & Knowledge Sharing
Python
SQL
CI/CD tools
Containerization (Docker)
Nice-to-have
Pharmaceutical commercial analytics
High-throughput inference
Incident management
Capacity planning
Reusable pipelines
Teamwork and multi-functional collaboration
Present complex findings
Key Requirements
3-6+ years in ML engineering or MLOps
Bachelor’s or Master’s degree in Computer Science, Data Science, or ML Engineering
Proven track record of deploying ML solutions at scale
Experience with end-to-end ML frameworks
Experience with unit and integration testing
Experience with model packaging and serving frameworks
Proficiency with distributed processing (Spark)
Understanding data privacy and security in healthcare