Senior Data Scientist – AI-Driven Data Center (Remote)

CloudData.Center; Stati Uniti; Remoto; USD 140.000 - 190.000; Tempo pieno

Vantaggi offerti da questo lavoro

Remote role

Descrizione del lavoro

CloudData.Center in the United States is seeking a data science professional to develop capabilities that help data center teams anticipate equipment issues, optimize energy use, and plan capacity. The role applies machine learning and digital twin approaches to operational telemetry, with models for real monitoring environments.

Responsibilities include building predictive maintenance models for power and cooling equipment, detecting anomalies in telemetry, creating energy optimization models,

Competenze

• 5+ years of data science, ML engineering, or applied AI in infrastructure or IoT settings.
• Proficiency in Python and a ML framework (scikit-learn, PyTorch, or TensorFlow).
• Experience with time-series anomaly detection and predictive maintenance.
• Familiarity with data center telemetry (DCIM, BMS, EPMS, SNMP, Modbus).
• Ability to communicate model findings to operational and executive audiences.

Mansioni

• Build predictive maintenance models for power and cooling equipment such as UPS systems.
• Detect anomalies in telemetry from facility platforms (DCIM, BMS, 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 via dashboards.
• Collaborate with facility operations to deploy models and explore generative AI applications.

Conoscenze

Python

Machine learning

Time-series

Communication

Formazione

5+ years data science / ML in infra or IoT

Strumenti

scikit-learn

TensorFlow

PyTorch

DCIM telemetry

Descrizione del lavoro

CloudData.Center in the United States is seeking a data science professional to develop capabilities that help data center teams anticipate equipment issues, optimize energy use, and plan capacity. The role applies machine learning and digital twin approaches to operational telemetry, with models for real monitoring environments.

Responsibilities include building predictive maintenance models for power and cooling equipment, detecting anomalies in telemetry, creating energy optimization models,