Bayesian Forecasting for Large-Scale Time-Series Data
Developed and deployed a Bayesian time-series forecasting model for national cell-tower traffic, improving prediction accuracy by 36% over the production baseline. The work combined statistical modeling, scalable data processing, and model evaluation for high-volume operational time-series data.
Focus areas: time-series forecasting, Bayesian modeling, model evaluation, production analytics, large-scale data
Technologies: Python, Bayesian inference, time-series modeling, statistical validation, production data pipelines
