Senior Data Scientist — AI-Driven Data Center Intelligence

Role overview

Develop data science capabilities that help data center teams anticipate equipment issues, improve energy use, and plan capacity. The work applies machine learning and digital twin approaches to operational telemetry, with models intended for use in real monitoring environments.

Responsibilities - Build predictive maintenance models for power and cooling equipment such as UPS systems. - Detect anomalies in telemetry from facility platforms, including DCIM, BMS, and EPMS. - Develop digital twin frameworks for facility visualization and simulation. - Create energy optimization models to improve efficiency and reduce cooling demand. - Forecast power, thermal, and space capacity needs, and present results through operational dashboards. - Work with facility operations teams to deploy models and explore generative AI applications.

Requirements - At least five years in data science, machine learning engineering, or applied AI in infrastructure or IoT settings. - Proficiency in Python and a machine learning framework such as scikit-learn, PyTorch, or TensorFlow. - Experience with time-series anomaly detection and predictive maintenance. - Familiarity with data center telemetry, including DCIM, BMS, EPMS, SNMP, or Modbus. - Ability to communicate model findings to operational and executive audiences.

Nice to have - Experience with digital twin platforms such as NVIDIA Omniverse or Azure Digital Twins. - MLOps experience with model deployment, monitoring, and retraining pipelines.

Benefits and work setup - Full-time, remote role; the listed locations are the United States or India.