Demographic Data Scientist

Apple is seeking a Demographic Data Scientist to join a human factors design team in Austin, TX (onsite). In this role, you will apply statistics, computer programming, and machine learning to translate human interaction data into visualizations that are actionable and intuitive, supporting improvements across Apple hardware products.

You will work closely with many cross-functional partners to examine datasets, answer targeted questions even when sample sizes are limited, and present results for dynamic problem spaces. Collaboration, clear communication, and a strong visual and analytical sensibility are central to the work.

Responsibilities

• Contribute to the development and continuing improvement of Apple hardware products by distilling human interaction data into actionable, intuitive visualizations.
• Collaborate with many cross-functional teams to work on the latest and most innovative Apple products.
• Apply statistics and visualization tools to answer specific questions about datasets regardless of sample size.
• Communicate solutions to dynamic problems through presentations.

Requirements

• Earned MS with +3 years of experience or a PhD in an analytical field, such as (but not limited to) Quantitive Social Sciences (Sociology, Education, Economics, Political Science), Computer Science, Engineering, Statistics, Geographic Information Systems, Applied Math, Physics, Biological Sciences, Climate or Environmental Science.
• Deep knowledge of statistical analysis and modeling tools, plus a strong foundation in linear algebra, geometry, optimization, or inference techniques.
• Strong programming skills in a scripting language such as Python, R, or Matlab (and similar), using these tools to model and visualize data for data-driven decision making.
• Excellent communication and interpersonal skills, with attention to detail, patience, and aesthetic sensibility.
• Demonstrated experience working in teams, including the willingness to solicit input and accept feedback.

Technologies

• Python
• R
• Matlab

Preferred Qualifications

• Experience making inferences from small-scale datasets.
• Experience with population modeling, inference, weighting, and simulation techniques such as Monte Carlo methods to understand and estimate variation and uncertainty.
• Experience with statistical methods including Bayesian approaches to identify trends and anomalies in multivariate and/or medium- and large-scale datasets.
• Experience with human anthropometric, biometric, or perception/preference data, and/or willingness to work with these data types.
• Experience using generative AI tools in workflows.