Data Science Architect – Data Center AI Operations

Codvo.ai; Pune District; On-site; INR 2,500,000 - 3,500,000; Full time

Job summary

An advanced technology firm is seeking a Data Science Architect to design the next-generation AI/ML platform for data center operations management. Responsibilities include architecting end-to-end AI/ML platforms, designing AIOps pipelines, and guiding data scientists on model design. Ideal candidates will have 14-18 years of experience, strong skills in time-series analysis and Python, and familiarity with important ML frameworks and industrial IoT analytics. This role is based in Pune, India.

Qualifications

• 14-18 years of experience; 5+ years in data science or ML architecture roles.
• Strong background in time-series analysis and anomaly detection.
• Experience in industrial IoT or critical infrastructure analytics is a plus.

Responsibilities

• Architect AI/ML platforms for data center operations.
• Design AIOps pipelines integrating data sources.
• Evaluate and standardize ML frameworks and production deployment.

Skills

Time-series analysis

Anomaly detection

Reinforcement learning

Python

ML frameworks

Cloud ML platforms

Tools

TensorFlow

PyTorch

XGBoost

Azure ML

AWS SageMaker

DCIM platforms

Job description

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