Data Science Architect – Data Center AI Operations

Codvo Private Limited; Pune District; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

An innovative tech company is seeking a Data Science Architect to define the AI/ML platform strategy for data center operations. This position requires extensive experience in data science, specifically in time-series analysis and anomaly detection, along with proficiency in Python and key ML frameworks. The role encompasses architecting end-to-end AI/ML solutions to optimize operations at a world-class data center. Familiarity with industry standards and tools is crucial for success.

Qualifications

• 14-18 years of experience with 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 or data center analytics is a plus.

Responsibilities

• Architect end-to-end AI/ML platforms for data center operations.
• Design AIOps pipelines integrating various data sources.
• Evaluate and standardize ML frameworks and MLOps tooling.

Skills

Time-series analysis

Anomaly detection

Reinforcement learning

Python

ML frameworks (TensorFlow/PyTorch/XGBoost)

Cloud ML platforms (Azure ML, AWS SageMaker)

Tools

DCIM platforms (Schneider EcoStruxure IT, Nlyte, or Sunbird)

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