Senior Data Scientist with Prophet, Python

We are seeking a Senior Data Scientist to build data-driven "should-cost" models that estimate what goods and services ought to cost, leveraging time-series and econometric methods to support procurement analytics. Responsibilities Develop "should-cost" models using time-series and econometric methods Incorporate macroeconomic factors and economic indicators as drivers of cost Model the relationships between commodity prices, spend data, and external economic variables Make model outputs explainable to stakeholders, showing which factors drive each cost estimate Apply time-series cross-validation techniques to ensure model robustness Prevent data leakage and overfitting in time-series models Distinguish between correlation and cointegration, and determine when each applies Select relevant features for time-series and econometric models Work with spend data and commodity price indexing to support procurement analytics Requirements 3+ years of experience in data science, with a focus on time-series and econometric modeling Proficiency in Python, Prophet, and Chronos Experience in procurement analytics, working with spend data and commodity price indexing Understanding of economic indicators, spend analysis, commodity pricing, and supplier diversity metrics Expertise in time-series cross-validation and explainable AI Proven ability to prevent data leakage and overfitting in time-series models Understanding of the difference between correlation and cointegration, and when each applies English proficiency at B2 level or higher