Senior Data Scientist, Hardware Quality

Role overview Use applied data science to improve the reliability and quality of connected consumer hardware. You’ll connect product, manufacturing, firmware, supplier, testing, and warranty data to identify why failures occur, anticipate risks, and help engineering teams make better design and launch decisions. The role spans data foundations, statistical analysis, machine learning, and technical leadership across distributed teams.

Responsibilities - Build reliability models for product performance, including warranty forecasts, degradation analysis, survival models, failure prediction, and field-performance cohorts. - Develop diagnostic and root-cause analysis methods that link telemetry and engineering data with manufacturing, supplier, testing, activation, and warranty records. - Work with hardware, quality, firmware, battery, manufacturing, supply chain, and support engineering teams to turn key risks into measurable analyses. - Analyze component, supplier, process, and build variation to identify quality drivers and inform corrective actions. - Create dependable data pipelines and analytical products that bring together hardware and operational data for recurring use. - Develop dashboards, monitoring, and decision-support tools that surface emerging risks and communicate practical recommendations.

Requirements - 6+ years of experience in data science, machine learning, reliability engineering, quality analytics, or a related quantitative field, with end-to-end ownership of significant problems. - Experience applying statistical modeling, machine learning, experimentation, or advanced analytics to reliability, quality, manufacturing, or another physical-product domain. - Ability to communicate technical findings clearly and influence engineering and business decisions. - Proven ability to make progress across distributed teams while requirements and data evolve.

Nice to have - Experience with consumer electronics, wearables, IoT, batteries, embedded systems, firmware, sensors, or connected devices. - Familiarity with manufacturing, supplier, component traceability, engineering test, or warranty data. - Background in battery degradation, runtime, power management, field-failure analysis, or predictive maintenance. - Familiarity with hardware development and launch stages such as EVT, DVT, and PVT.

Benefits and work setup - Remote role within the US, with a preference for candidates near San Francisco. - Salary and equity, health and dental coverage, mental health resources, paid leave, and an employee device are offered. Pay varies by location; listed salary bands range from $147,900 to $203,000 depending on region.