Data Science Architect – Data Center AI Operations
Data Science Architect – Data Center AI Operations
We are looking for a Data Science Architect to design and own the AI/ML platform strategy for next-generation data center operations management. This role will define how intelligence is embedded into infrastructure operations management for a world-class hyperscale data center operator.
Key Responsibilities
- Architect end-to-end AI/ML platforms for data center operations: predictive maintenance, thermal optimization, power efficiency (PUE/WUE), and capacity planning
- Design AIOps pipelines integrating DCIM, BMS, SCADA, and CMDB data sources
- Evaluate and standardize ML frameworks, feature stores, model registries, and MLOps tooling
- Guide data scientists on model design, validation methodology, and production deployment
- Define data quality, lineage, and observability standards for operational data
- Engage with CyrusOne stakeholders to translate operational challenges into AI use cases and roadmaps
Must-Have Profile
- 14-18 years; 5+ years in data science / ML architecture roles
- Strong background in time-series analysis, anomaly detection, or reinforcement learning for physical systems
- Experience in industrial IoT, data center, or critical infrastructure analytics is a strong plus
- Proficient in Python, ML frameworks (TensorFlow/PyTorch/XGBoost), and cloud ML platforms (Azure ML, AWS SageMaker)
- Familiarity with DCIM platforms (Schneider EcoStruxure IT, Nlyte, or Sunbird) desirable
Note- Please apply via our official careers portal only, as applications sent directly to executives may not be considered.
