Own and evolve key forecasting assets, applying modern statistical, machine learning, and AI-driven approaches to improve accuracy, scalability, and business value
Integrate AI into forecasting workflows, such as feature engineering, exploratory data analysis, and model development
Shape next-generation forecasting capabilities while driving measurable impact across the organization
Requirements
3+ years of experience in data science, forecasting, or a related quantitative field
Strong expertise in time series forecasting methods, including statistical and machine learning approaches
Experience with ensemble modeling techniques and model evaluation strategies
Proven experience with hierarchical or multi-level forecasting
Strong programming skills in Python (e.g., pandas, NumPy, scikit-learn, statsmodels, or similar libraries)
Experience applying AI/ML techniques to forecasting workflows, including feature engineering and exploratory data analysis
Strong problem-solving, communication, and stakeholder management skills