Data-Driven Supply & Demand Analytics Lead

Apple, Inc.; Austin (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Apple Austin, Texas-based data analytics role is seeking a skilled data scientist/analyst to transform complex retail supply chain data into actionable insights. You’ll design and deploy ETL pipelines, predictive models, and interactive dashboards using Python, SQL, Streamlit, and Tableau to guide inventory and fulfillment decisions.

You will collaborate with cross-functional teams, optimize reporting processes, and automate data workflows at scale, contributing to strategic business outcomes in

Qualifications

• Bachelor’s degree in a quantitative field and 3+ years of related experience.
• Proficient in Python for ETL, data processing, and modeling.
• Strong SQL skills with multiple databases and cloud platforms.
• Experience building ML models for forecasting and analytics.
• Ability to develop interactive data apps and dashboards.

Responsibilities

• Transform datasets into insights with data-driven storytelling for supply chain.
• Develop predictive models for store forecasting and inventory optimization.
• Build interactive web apps using Streamlit for operational decision support.
• Collaborate with cross-functional teams and senior leadership to drive decisions.

Skills

Python (pandas, NumPy)

SQL (Snowflake, MySQL)

Machine learning (scikit-learn, XGBo​o

Streamlit apps

Tableau visualization

ETL pipelines

RESTful APIs

Git/GitHub

Data analysis

Education

Bachelor’s degree in Data Science, Statistics, Computer Science, or related field

Tools

Snowflake

MySQL

Streamlit

Tableau

Git

Job description

Apple Austin, Texas-based data analytics role is seeking a skilled data scientist/analyst to transform complex retail supply chain data into actionable insights. You’ll design and deploy ETL pipelines, predictive models, and interactive dashboards using Python, SQL, Streamlit, and Tableau to guide inventory and fulfillment decisions.

You will collaborate with cross-functional teams, optimize reporting processes, and automate data workflows at scale, contributing to strategic business outcomes in