Data Scientist – Data Center Intelligence

We are a global empathy-led technology services company where software and people transformations go hand-in-hand. Product innovation and mature software engineering are part of our core DNA.

Our mission is to help our customers accelerate their digital journeys through a global, diverse, and empathetic talent pool following outcome-driven agile execution. Respect, Fairness, Growth, Agility, and Inclusiveness are the core values that we aspire to live by each day.

We continue to invest in our digital strategy, design, cloud engineering, data, and enterprise AI capabilities required to bring a truly integrated approach to solving our clients' most ambitious digital journey challenges.

About This Role

Build and deploy predictive models that make data center operations smarter, safer and more energy-efficient. You will work with sensor telemetry, DCIM feeds, and operational logs to generate actionable intelligence for site operations teams.

Key Responsibilities

Develop ML models for anomaly detection, predictive failure analysis, cooling optimization, and capacity forecasting

Work with time-series data from BMS, SCADA, PDUs, and environmental sensors

Build, validate and productionize models using MLflow, Azure ML, or SageMaker

Collaborate with data engineers for feature engineering and pipeline design

Create dashboards and reports translating model outputs into actionable operations insights

Conduct A/B testing and model performance monitoring in production environments

Must-Have Profile

4-9 years; strong foundation in statistical ML and Python-based data science stack

Proficiency in scikit-learn, XGBoost, PyTorch or TensorFlow; experience with time-series forecasting (Prophet, LSTM, ARIMA)

Familiarity with IoT/OT data (sensor streams, telemetry, irregularly-sampled data) a strong plus

Experience with PUE optimization, thermal modeling, or critical infrastructure analytics highly desirable\

Note- Please apply via our official careers portal only, as applications sent directly to executives may not be considered.