Back
Mid-level, metro location and known consumer brand balanced by specialized forecasting requirements.
Forecasting and supply-chain ML skills are somewhat specialized but transferable across industries.
Explicit 4–6 years plus mandatory forecasting, ML, and production/MLOps skills creates strict shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop, implement, and improve demand forecasting algorithms using Python and SQL, including model testing, computational experiments, and hyperparameter tuning.
Collaborate with software engineers and business stakeholders to understand business context, explain forecast models to users, and build trust in forecasting outputs.
Lead and mentor junior data scientists, manage workflows, review designs, and contribute subject matter expertise in machine learning for forecasting and demand planning.
Master's degree in Data Science, Statistics, Applied Mathematics or Bachelor's in Engineering, Computer Science, or related field.
4 to 6 years of total work experience in data science or analytical roles, with at least 2-3 years in time series forecasting.
Advanced programming skills in Python and SQL; experience with statistical/programming tools (e.g., R, Hadoop/Hive, Scala).
Strong knowledge of time series forecasting techniques, feature engineering, hyperparameter optimization, and ability to write clean, maintainable code.
Experienced in demand forecasting and supply chain domains, preferably within CPG or healthcare industries.
Able to bridge technical and business teams; effective communicator who can explain complex models to non-technical users to build trust.
Proven capability to lead data science teams, drive technical decisions, implement ML operations including CI/CD pipelines, and apply AI/ML in operational environments.