Demographic Data Scientist

Apple is seeking a Demographic Data Scientist to join its human factors design team in Austin, Texas, onsite. This role focuses on studying human populations through statistics, programming, and machine learning to inform product design decisions. It’s a collaborative, cross-disciplinary position that translates data into actionable insights for diverse user groups.

Responsibilities

• Develop scripts to preprocess data from multiple sources, ensuring data integrity and quality.
• Explore new data sources that can extend insights and enhance analyses.
• Perform data exploration, QA/QC, visualization, statistical analyses, and mathematical modeling.
• Build custom visualizations that enable decision makers to grasp findings quickly.
• Collaborate with cross-functional teams to identify trends and create tools that simplify future analysis and visualization.
• Construct statistical or machine learning models to characterize human variation across populations.

Requirements

• MS with three or more years of experience or PhD in an analytical field such as quantitative social sciences, computer science, engineering, statistics, geographic information systems, applied mathematics, physics, biological sciences, climate or environmental science.
• Solid knowledge of statistical analysis and modeling tools, with a strong foundation in linear algebra, geometry, optimization, or inference techniques.
• Proficiency in scripting languages (Python, R, MATLAB, etc.) to model and visualize data for data‑driven decision making.
• Excellent communication and interpersonal skills, attention to detail, patience, and an aesthetic sense.
• Experience working in teams and collaborating with peers, with a willingness to solicit input and accept feedback.

Technologies

• Python
• R
• MATLAB
• Generative AI tools

Description

In this team‑oriented, collaborative environment, you will contribute to Apple’s frontier products alongside multiple cross‑functional teams. The role values curiosity and a willingness to apply diverse methods to ambiguous problems and to translate complex data into practical insights.

Success in this position means fluency with statistics and visualization tools to answer specific questions about datasets of varying sizes, and a talent for communicating solutions to dynamic challenges through clear, compelling presentations.

Preferred Qualifications

• Experience making inferences from small-scale datasets.
• Background in population modeling, inference, weighting, and simulation techniques such as Monte Carlo methods to understand variation and uncertainty.
• Experience with Bayesian methods to identify trends and anomalies in multivariate and/or large datasets.
• Familiarity with human anthropometric, biometric, or perception/preference data, or a willingness to explore these data types.
• Experience incorporating generative AI tools into workflows.

Minimum Qualifications

• MS with three or more years of experience or PhD in an analytical field such as quantitative social sciences, computer science, engineering, statistics, GIS, applied mathematics, physics, biological sciences, or climate/environmental science.
• Deep knowledge of statistical analysis and modeling tools, with a strong foundation in linear algebra, geometry, optimization, or inference techniques.
• Strong programming skills in a scripting language (Python, R, MATLAB, etc.) to model and visualize data for data‑driven decision making.
• Excellent communication and interpersonal skills, attention to detail, patience, and aesthetic sensibility.
• Demonstrated experience working in teams and collaborating with peers, with a willingness to solicit input and accept feedback.