Job Opportunities API

Requirements Proficiency in Python and PySpark for data analysis, machine learning, and demand forecasting (regression + time series models) Experience with forecasting models such as LightGBM/ XGBoost and classical time series methods (e.g., ETS/ARIMA ) Strong understanding of the machine learning workflow ( data cleansing, feature engineering, model evaluation, model explainability ) Familiarity with forecasting evaluation metrics (e.g. MAPE, MAE ) and ability to validate model performance Strong SQL skills for managing and querying large datasets Knowledge of data visualization tools (e.g., Power BI ) Experience with cloud-based technologies such as Databricks, Azure, or AWS Strong communication skills — able to explain insights and models to both business and technical teams Ownership and accountability — able to deliver end-to-end solutions, not just analysis Collaboration — able to work effectively with Data Engineering, Tech, Product, and Supply Chain teams Preferred (Optional) Qualifications: Exposure to MLOps tools (e.g., MLflow , job scheduling) Experience building production pipelines for forecast outputs (daily/weekly runs) and supporting downstream systems Experience in real-time analytics or scheduled processing systems Optimization mindset — able to balance accuracy, business impact, and time constraints Benefits Clear focus. Diverse Workplace (Our members are from around the world!) Non-hierarchical and agile environment Growth opportunity and career path