Supply Demand Planning

Apple•Austin, TX

About The Position

Apple Inc. is hiring for a Supply Demand Planning role in Austin, Texas. The position transforms complex datasets into business insights and supports data-driven decision-making across the retail supply chain. It involves creating sophisticated models and interactive visualizations, collaborating with cross-functional stakeholders to understand domain requirements, applying data science to uncover insights, and implementing automation to improve team efficiency. The role communicates findings and business impact to senior leadership and works effectively in a fast-paced, ambiguous environment. The position uses advanced Python and SQL to develop machine-learning algorithms that assess supply-chain performance, detect issues, and support proactive resolutions. It also builds applications using Streamlit, Python, and prompt engineering to improve team efficiency and accuracy. The role is 40 hours per week.

Requirements

Bachelor’s degree or foreign equivalent in Logistics and Supply Chain Management, Quantitative Management, or a related field.
Three years of experience in the job offered or a related occupation.
Three years of experience using Python, including pandas, NumPy, and multiprocessing, to develop automated ETL pipelines consolidating retail supply-chain data from multiple enterprise sources.
Three years of experience writing and optimizing complex SQL queries using multi-table joins, window functions, and aggregation logic in relational and cloud-based platforms, including Snowflake and MySQL.
Three years of experience developing predictive supply-chain store-supply forecasting models with Python libraries such as scikit-learn or XGBoost, including feature engineering, time-series model training, and forecast-accuracy evaluation.
Three years of experience building Python and Streamlit web applications for operational decision support, including data upload interfaces, user data logging, session-state management, and real-time enterprise data integration.
Three years of experience using Tableau and Python visualization libraries such as Plotly or Matplotlib to create dashboards and automated reporting for inventory health, service levels, and fulfillment rates.
Three years of experience designing scheduled Python and Jupyter notebook data pipelines for recurring reporting, including extraction, transformation, validation, and multi-channel distribution.
Three years of experience generating formatted, multi-sheet Excel workbooks with Python libraries such as openpyxl and XlsxWriter, including calculated fields, conditional formatting, and business logic.
Three years of experience integrating enterprise systems through Python REST APIs, Tableau Server integration, cloud-storage APIs, and webhook-based messaging, including secure credential management, error handling, and retry logic.
Three years of experience using Git and GitHub for collaborative, version-controlled analytics development, including branch management, pull requests, code documentation, and reproducible pipeline logic.
Three years of experience designing and deploying machine-readable API connectors and structured knowledge databases for AI-assisted analytics, including RAG modeling, natural-language query interfaces, and automated data retrieval.

Responsibilities

Transform complex datasets into business insights using creativity, technical skills, and strategic focus.
Develop data-driven models and interactive visualizations to explain retail supply-chain dynamics.
Collaborate with cross-functional stakeholders to understand domain-specific requirements.
Apply data science to uncover insights, inform decisions, and implement automation that eliminates non-value-added tasks.
Communicate findings and business impact to senior leadership to guide strategic choices.
Use Python and SQL to develop machine-learning algorithms that assess supply-chain performance, detect issues, and support proactive resolutions.
Build Streamlit and Python applications using prompt engineering to improve team efficiency and accuracy.
Develop Python ETL pipelines that consolidate retail supply-chain data from enterprise sources for inventory and fulfillment analysis.
Write and optimize SQL queries in Snowflake and MySQL to analyze inventory, demand planning, and shipment data.
Develop and evaluate predictive machine-learning models for store supply forecasting.
Build interactive Streamlit applications for operational decision support, including data upload, user logging, session-state management, and enterprise data integration.
Create analytical dashboards and automated reporting pipelines for supply-chain performance metrics using Tableau and Python visualization libraries.
Design scheduled data pipelines for recurring reporting, including extraction, transformation, validation, and distribution through email, cloud storage, and messaging platforms.
Generate and update formatted, multi-sheet Excel workbooks programmatically for supply-chain planning and inventory control analysis.
Integrate enterprise data systems through REST APIs, Tableau Server integration, cloud-storage APIs, and webhook-based messaging services, with secure credential management, error handling, and retry logic.
Use Git and GitHub for collaborative, version-controlled development, including branch management, pull requests, documentation, and reproducible pipeline logic.
Design and deploy machine-readable API connectors and structured knowledge databases for AI-assisted supply-chain analytics, including RAG modeling, natural-language query interfaces, and automated data retrieval.