Supply Demand Planning

Apple • Austin, TX

1h

About The Position

Apple Inc. is hiring for a position in Austin, Texas, focused on transforming complex datasets into business insights for the retail supply chain. The role uses data science, analytics, modeling, and interactive visualizations to clarify supply chain dynamics and support informed decision-making. It partners with cross-functional stakeholders to understand domain requirements and implements automation to improve team efficiency by eliminating non-value-added tasks. The position communicates findings and business impact to senior leadership and works effectively amid ambiguity in a fast-paced environment. It also uses Python, SQL, machine learning, Streamlit, and prompt engineering to identify supply chain performance issues, support proactive resolutions, and build tools that improve team efficiency and accuracy. The position is 40 hours per week.

Requirements

• Bachelor’s degree or foreign equivalent in Logistics and Supply Chain Management, Quantitative Management, or a related field.
• At least 3 years of experience in the job offered or a related occupation.
• At least 3 years of experience using Python, including pandas, NumPy, and multiprocessing libraries, to build ETL pipelines that consolidate retail supply chain data from multiple enterprise sources for inventory and fulfillment analysis.
• At least 3 years of experience writing and optimizing complex SQL queries on relational and cloud-based database platforms, including Snowflake and MySQL, using multi-table joins, window functions, and aggregation logic to analyze inventory, demand planning, and shipment data.
• At least 3 years of experience developing predictive machine learning models in Python, using libraries such as scikit-learn or XGBoost, for store supply forecasting, including feature engineering, time-series model training, and forecast accuracy evaluation.
• At least 3 years of experience building interactive Python and Streamlit applications for operational decision support, including data upload interfaces, user data logging, session state management, and real-time enterprise data integration.
• At least 3 years of experience using Tableau and Python visualization libraries such as Plotly or Matplotlib to create analytical dashboards and automated reporting for retail supply chain metrics, including inventory health, service levels, and fulfillment rates.
• At least 3 years of experience designing scheduled Python and Jupyter notebook data pipelines for recurring supply chain reporting, including extraction, transformation, validation, and distribution through email, cloud storage, and messaging platforms.
• At least 3 years of experience programmatically generating and updating formatted, multi-sheet Excel workbooks using Python libraries such as openpyxl and XlsxWriter, with calculated fields, conditional formatting, and business logic for supply chain planning and inventory control analysis.
• At least 3 years of experience integrating enterprise data systems with Python RESTful API connectors, including Tableau Server integration, cloud storage APIs, and webhook-based messaging services, with secure credential management, error handling, and retry logic.
• At least 3 years of experience using Git and GitHub for collaborative, version-controlled analytics development, including branch management, pull requests, code documentation, and reproducible data pipeline logic.
• At least 3 years of experience designing and deploying machine-readable API connectors and structured knowledge databases for AI-assisted supply chain analytics, including Retrieval Augmented Generation (RAG), natural-language query interfaces, and automated data retrieval pipelines.

Responsibilities

• Transform complex datasets into business insights for the retail supply chain.
• Develop sophisticated models and interactive visualizations to illuminate retail supply chain dynamics.
• Collaborate with cross-functional stakeholders to understand domain-specific requirements.
• Apply data science to uncover insights and support informed decision-making.
• Implement automation initiatives to improve team efficiency and eliminate 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 applications using Streamlit, Python, and prompt engineering to improve team efficiency and accuracy.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level