Overview
Work as a Supply Chain Data Scientist to build and deploy forecasting and predictive analytics solutions for demand and supply planning. Use time-series forecasting, machine learning, and visualization to improve planning accuracy, responsiveness, and operational efficiency.
What you'll do
- Develop and deploy time-series forecasting models for demand planning across products and regions.
- Build and evaluate machine learning models for demand sensing, anomaly detection, and predictive analytics.
- Wrangle and engineer features and perform exploratory analysis on large-scale supply chain datasets.
- Design and implement end-to-end data science pipelines for forecasting and predictive use cases.
- Analyze and monitor forecast performance metrics (accuracy, bias, attainment) and improve model performance.
- Translate data insights into actionable recommendations for business stakeholders.
- Create documentation, dashboards, and visualizations to communicate insights and outputs.
What you'll need
- Strong foundation in time-series forecasting methods (ARIMA, Prophet, XGBoost, and other ML-based approaches).
- Experience applying machine learning to real-world business problems in demand forecasting or predictive analytics.
- Proficiency in Python, SQL, Excel (PowerPivot), and PowerPoint for building, testing, visualizing, and presenting models.
- Understanding of data ecosystems, including relational databases, data-warehouse design, cloud storage, and ETL best practices.
- Experience with GitHub and cloud compute/ML platforms such as AWS SageMaker, Microsoft Azure, Google Cloud, Kubeflow, or Databricks.
- Project management and cross-functional collaboration experience to deliver optimization and analytics initiatives.
Nice to have
- Master’s degree in data science, statistics, computer science, or a related field.
- Experience with large-scale forecasting systems and demand planning processes.
- Familiarity with feature engineering for time-series and hierarchical forecasting techniques.
- Proven track record of delivering measurable improvements in forecast accuracy or business KPIs.
Details
- Expected flexibility to collaborate with U.S.-based teams and support work aligned to U.S. time zones when needed.
FullTime
Negotiable
Posted this week
5 - 7 Years
