Data Scientist Data Center Intelligence

As a Data Scientist at the global empathy-led technology services company, you will play a crucial role in building and deploying predictive models to enhance data center operations. Your responsibilities will include: - Developing ML models for anomaly detection, predictive failure analysis, cooling optimization, and capacity forecasting. - Working with time-series data from BMS, SCADA, PDUs, and environmental sensors. - Building, validating, and productionizing models using MLflow, Azure ML, or SageMaker. - Collaborating with data engineers for feature engineering and pipeline design. - Creating dashboards and reports to translate model outputs into actionable operations insights. - Conducting A/B testing and monitoring model performance in production environments. To be successful in this role, you must have: - 4-9 years of experience with a strong foundation in statistical ML and Python-based data science stack. - Proficiency in scikit-learn, XGBoost, PyTorch or TensorFlow, with experience in time-series forecasting (Prophet, LSTM, ARIMA). - Familiarity with IoT/OT data such as sensor streams, telemetry, and irregularly-sampled data is a strong plus. - Experience in PUE optimization, thermal modeling, or critical infrastructure analytics is highly desirable. Please apply via the official careers portal only, as applications sent directly to executives may not be considered. As a Data Scientist at the global empathy-led technology services company, you will play a crucial role in building and deploying predictive models to enhance data center operations. Your responsibilities will include: - Developing ML models for anomaly detection, predictive failure analysis, cooling optimization, and capacity forecasting. - Working with time-series data from BMS, SCADA, PDUs, and environmental sensors. - Building, validating, and productionizing models using MLflow, Azure ML, or SageMaker. - Collaborating with data engineers for feature engineering and pipeline design. - Creating dashboards and reports to translate model outputs into actionable operations insights. - Conducting A/B testing and monitoring model performance in production environments. To be successful in this role, you must have: - 4-9 years of experience with a strong foundation in statistical ML and Python-based data science stack. - Proficiency in scikit-learn, XGBoost, PyTorch or TensorFlow, with experience in time-series forecasting (Prophet, LSTM, ARIMA). - Familiarity with IoT/OT data such as sensor streams, telemetry, and irregularly-sampled data is a strong plus. - Experience in PUE optimization, thermal modeling, or critical infrastructure analytics is highly desirable. Please apply via the official careers portal only, as applications sent directly to executives may not be considered.