Data Science Architect Data Center AI Operations (Pune)

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 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
• Solid 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

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 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
• Solid 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.