Lead Data Scientist with Prophet, Python
We're looking for a Lead Data Scientist to create data-driven "should-cost" models that predict fair pricing for goods and services, using time-series and econometric approaches to power procurement analytics.
Responsibilities
- Build "should-cost" models through time-series and econometric methods
- Integrate macroeconomic factors and economic indicators as cost drivers
- Model relationships linking commodity prices, spend data, and external economic variables
- Ensure model outputs are interpretable to stakeholders by highlighting the factors behind each cost estimate
- Use time-series cross-validation techniques to guarantee model reliability
- Guard against data leakage and overfitting within time-series models
- Differentiate between correlation and cointegration, identifying when each is applicable
- Choose appropriate features for econometric and time-series models
- Utilize spend data and commodity price indexing to enhance procurement analytics
Requirements
- 5+ years in data science, specializing in econometric and time-series modeling
- Skilled in Python, Prophet, and Chronos
- Background in procurement analytics, including spend data and commodity price indexing
- Knowledge of economic indicators, spend analysis, commodity pricing, and supplier diversity metrics
- Strong command of time-series cross-validation and explainable AI
- Demonstrated skill in preventing data leakage and overfitting in time-series models
- Clear grasp of the distinction between correlation and cointegration, and their respective use cases
- B2-level English proficiency or above
