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.

Data Science Architect Data Center AI Operations

Job Description

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