Senior Data Scientist — AI-Driven Data Center Intelligence

CloudData.Center; EE. UU.; A distancia; USD 140.000 - 190.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote role

Descripción de la vacante

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,

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Python

Machine learning

Time-series

Communication

Educación

5+ years data science / ML in infra or IoT

Herramientas

scikit-learn

TensorFlow

PyTorch

DCIM telemetry

Descripción del empleo

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.