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
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Architect end-to-end AI/ML platforms for data center operations: predictive maintenance, thermal optimization, power efficiency (PUE/WUE), and capacity planning
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Design AIOps pipelines integrating DCIM, BMS, SCADA, and CMDB data sources
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Evaluate and standardize ML frameworks, feature stores, model registries, and MLOps tooling
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Guide data scientists on model design, validation methodology, and production deployment
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Define data quality, lineage, and observability standards for operational data
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Engage with stakeholders to translate operational challenges into AI use cases and roadmaps
Must-Have Profile
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14-18 years; 5+ years in data science / ML architecture roles
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Strong background in time-series analysis, anomaly detection, or reinforcement learning for physical systems
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Experience in industrial IoT, data center, or critical infrastructure analytics is a strong plus
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Proficient in Python, ML frameworks (TensorFlow/PyTorch/XGBoost), and cloud ML platforms (Azure ML, AWS SageMaker)
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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.
