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.

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 stakeholders to translate operational challenges into AI use cases and roadmaps

Requirements

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; Proficient in Python, ML frameworks (TensorFlow/PyTorch/XGBoost), and cloud ML platforms (Azure ML, AWS SageMaker)

Nice to have

Experience in industrial IoT, data center, or critical infrastructure analytics; Familiarity with DCIM platforms (Schneider EcoStruxure IT, Nlyte, or Sunbird)