Data Scientist at Apple

San Diego, California, United States -

Full Time

Start Date

Immediate

Expiry Date

26 Jun, 26

Salary

0.0

Posted On

28 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Quality Engineering, Algorithm Evaluation, Test Strategy, Signal-Level Sensor Algorithms, Statistical Methods, A/B Testing, Regression Analysis, Significance Testing, Python, Data Exploration, Test Scenario Frameworks, Benchmarking, ML, UX Research, Causal Inference, Experimental Design

Industry

Computers and Electronics Manufacturing

Description

Join Apple's HID Quality Engineering team to ensure our products exceed our customers' expectations! You'll 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. DESCRIPTION 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. MINIMUM QUALIFICATIONS MS in EE, ECE, CS, Statistics, HCI, Cognitive Science, or a related field 5+ years of experience in quality engineering, test strategy, or algorithm/ML evaluation Experience writing quality specifications or test plans for complex technical systems adopted by multiple teams Experience with signal-level sensor algorithms Familiarity with statistical methods used in algorithm evaluation, such as A/B testing, regression analysis, and significance testing Working proficiency with Python for data exploration and analysis PREFERRED QUALIFICATIONS PhD in EE, ECE, CS, Statistics, HCI, Cognitive Science, or a related field Strong 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 changing Experience defining test scenario coverage models and setting benchmarks for systems where ground truth is ambiguous or user-dependent Experience building consensus on quality standards across teams with competing priorities Ability to write specifications precise enough for engineers to implement automation directly, without ambiguity Background in UX research, HCI, or human factors, with experience grounding technical quality definitions in human behavior Familiarity with embedded platform constraints Experience with causal inference or advanced experimental design for algorithm evaluation

Responsibilities

This role focuses on defining algorithm quality by writing quality specifications, establishing benchmarks, and developing test scenario frameworks. The individual will partner with various teams to ensure new customer-facing algorithms are effectively validated using data and repeatable processes.