Data Scientist

Join Apples HID Quality Engineering team to ensure our products exceed our customers expectations! Youll work with QE and Algorithm teams to build metrics around algorithm performance turning user behavior into quality specifications and measurable standards that teams can consistently apply. You will make sure new customer facing algorithms are validated effectively using data and repeatable processes. This includes defining the right data ensuring quality of data and labeling and running tests on datasets.

This role is focused on defining algorithm quality. Day-to-day work involves writing quality specifications establishing benchmarks developing test scenario frameworks and partnering closely with algorithm platform and UX research teams to identify where quality standards are missing or misaligned with user outcomes.

Write quality specifications that translate real user needs and device constraints into testable technical requirementsnEstablish acceptance criteria and benchmarks for touch algorithm families including clear definitions of meaningful regression versus noisenBuild structured test scenario libraries and coverage models reflecting the diversity of real-world touch interactions and user conditionsnIdentify gaps between current validation approaches and user-relevant edge casesnDesign data collection labeling and analysis plans that enable effective validation and spec settingnEmbed with algorithm teams to understand their workflows and surface gaps where quality is undefined inconsistently applied or disconnected from user impactnTranslate user research and field data into concrete quality requirements establishing shared language for what validated means at each stage of developmentnProvide platform and automation teams with a prioritized set of automation requirements grounded in written quality specificationsnDrive adoption of quality frameworks and build consensus across teams with different algorithms timelines and constraints

BS in EE ECE CS Statistics HCI Cognitive Science or a related fieldn3 years of experience in quality engineering test strategy or algorithm/ML evaluationnExperience writing quality specifications or test plans for complex technical systems adopted by multiple teamsnExperience with signal-level sensor algorithmsnFamiliarity with statistical methods used in algorithm evaluation such as A/B testing regression analysis and significance testingnWorking proficiency with Python for data exploration and analysis

MS or PhD in EE ECE CS Statistics HCI Cognitive Science or a related fieldnStrong understanding of ML and sensing system behavior with the ability to reason about failure modes edge cases and the difference between a metric shifting and quality actually changingnExperience defining test scenario coverage models and setting benchmarks for systems where ground truth is ambiguous or user-dependentnExperience building consensus on quality standards across teams with competing prioritiesnAbility to write specifications precise enough for engineers to implement automation directly without ambiguitynBackground in UX research HCI or human factors with experience grounding technical quality definitions in human behaviornFamiliarity with embedded platform constraintsnExperience with causal inference or advanced experimental design for algorithm evaluation