Data and Applied Scientist
Core
Developing production-grade statistical and machine learning models for global cloud infrastructure capacity planning and demand forecasting.
Role type
Senior Applied Scientist (Forecasting & Optimization)
Builds
Production ML models for cloud demand planning and supply chain optimization
Domain
Cloud Infrastructure / Supply Chain Management
Deliverable
production ML models
Required skills
Time series forecasting, Statistical modeling, Machine learning (R/Python), SQL, Big data processing (Hadoop/Spark/Databricks), Feature engineering, Optimization modeling
Preferred skills
Deep learning (TensorFlow/PyTorch), Operations research, Supply chain modeling, Git version control
Technologies
Python, R, scikit-learn, numpy, pandas, statsmodel, SQL, Hadoop, Spark, Databricks, TensorFlow, PyTorch, CNTK
Responsibilities
Research and develop production-grade forecasting and anomaly detection models; Manage large volumes of data and refine data sources through feature engineering; Deploy models to drive cloud infrastructure capacity planning; Analyze data to identify trends and improve existing forecasting models; Lead collaboration to apply state-of-the-art algorithms to business problems; Provide coaching on business context and methodological rigor.
Seniority
Senior, hands-on IC with team leadership
