About the position
Apple is currently seeking an enthusiastic team player to join a dynamic and collaborative group as a data scientist focusing on demography within a human factors design team. You’ll have the unique opportunity to contribute to the development and continuing improvement of Apple hardware products by distilling data into actionable and intuitive visualizations from a human interaction perspective. You will collaborate closely with cross-functional team members.
Responsibilities
- Write scripts to pre-process data from various sources and formats.
- Process, clean, and verify the integrity of data.
- Investigate new sources that can extend and improve insights.
- Conduct data exploration on datasets, QA/QC, visualization, statistical and data analyses, and mathematical modeling.
- Create custom visualizations that help decision makers quickly understand the data.
- Collaborate with cross-functional teams to help identify trends in their data or to build tools that will enable easier analysis and visualizations in the future.
Requirements
- Masters degree or higher in an analytical field such as Social Sciences, Computer Science, Engineering, Statistics, Geographic Information Systems, Applied Math, Physics, Biological Sciences, Climate or Environmental Science.
- Deep knowledge of statistical analysis and modeling tools.
- Strong foundation in linear algebra, geometry, optimization, or inference techniques.
- Strong programming skills in a scripting language (Python, R, Matlab, etc).
- Excellent communication and interpersonal skills.
- Attention to detail, patience, and aesthetic sensibility.
- Demonstrated experience working in teams and collaborating with peers.
Nice-to-haves
- Experience with population modeling, inference, weighting, and simulation techniques (e.g. Monte Carlo methods).
- Experience using statistics to identify trends and anomalies in multivariate and/or medium-sized and/or large-scale datasets.
- Experience with human anthropometric, biometric, or perception/preference data.
