Senior Data Scientist, Hardware Quality

ŌURA

1d • $147,900 - $203,000 • Remote

About The Position

ŌURA is seeking an experienced Senior Data Scientist to partner with Hardware, Quality, Firmware, Manufacturing, Supply Chain, Support Engineering, and Finance teams. The role will build data science and decision systems to improve hardware reliability, from early product testing and launch readiness through field performance, warranty outcomes, and long-term product improvement.

This full-stack applied data science role combines data foundations, statistical modeling, machine learning, experimentation, and cross-functional technical leadership. The work focuses on understanding product failures, predicting reliability issues, connecting manufacturing and testing data to field outcomes, and turning complex engineering data into clear decisions. This is a remote US role, with a slight preference for candidates based in San Francisco.

Requirements

• At least 6 years of experience in data science, machine learning, reliability engineering, quality analytics, or a closely related quantitative field, with a record of owning high-impact problems end to end.
• Experience applying statistical modeling, machine learning, experimentation, or advanced analytics to reliability, quality, manufacturing, hardware, IoT, electronics, automotive, medical devices, or another physical-product domain.
• Strong experience with reliability and time-to-event methods, such as survival analysis, hazard modeling, accelerated-life testing, degradation modeling, or warranty forecasting.
• Strong proficiency in SQL and Python, including experience building analytical data models, statistical or machine-learning workflows, and production-quality measurement systems.
• Data-engineering intuition and experience unifying and transforming data from multiple operational and technical systems into reliable datasets for analysis and modeling.
• Experience with noisy, incomplete, longitudinal, or high-volume telemetry and test data, and sound judgment in distinguishing data artifacts from meaningful product signals.
• Experience designing experiments or observational analyses to support technical decisions, including understanding confounding, bias, uncertainty, and validation.
• Experience with modern cloud and data platforms such as Databricks, AWS, dbt, Snowflake, or similar tools.
• Ability to clearly communicate complex analytical concepts to engineers, quality and operations partners, product leaders, and executives.
• Ability to work effectively across distributed, cross-functional teams and drive progress while requirements and data are evolving.

Nice To Haves

• Experience with consumer electronics, wearables, IoT, batteries, embedded systems, firmware, sensors, or connected devices.
• Experience analyzing manufacturing, supplier, component traceability, MES, ERP, engineering test, or warranty data.
• Experience with battery degradation, runtime modeling, charging optimization, power management, or electronics reliability.
• Experience building field-failure analysis, anomaly detection, predictive-maintenance, or early-warning systems.
• Familiarity with hardware development and launch processes, including EVT, DVT, PVT, and field-test programs.

Responsibilities

• Build and evolve reliability and quality models for current and next-generation Oura Ring products, including warranty forecasts, runtime degradation, survival analysis, failure-mode prediction, and cohort-based field-performance analysis.
• Develop diagnostics and root-cause analysis systems connecting ring telemetry, firmware and engineering diagnostics, manufacturing records, supplier and component data, testing results, activations, and warranty outcomes.
• Partner with Hardware, Quality, Firmware, Battery Engineering, Manufacturing, Supply Chain, and Support Engineering to identify high-leverage reliability risks and translate them into measurable analytical problems.
• Analyze component, supplier, manufacturing-process, and ring-build variation to identify product-quality drivers and inform corrective actions, design decisions, and supplier-quality improvements.
• Build analytical data products and pipelines that unify hardware, manufacturing, firmware, diagnostic, activation, and warranty data for recurring analysis and decision-making.
• Develop production AI-enhanced dashboards, monitoring, and decision-support tools that surface emerging failure risks and provide actionable recommendations to technical and executive stakeholders.
• Establish measurement practices for hardware quality, including metric definitions, cohorting, normalization, uncertainty, data-quality checks, and appropriate statistical methods.
• Translate technical findings into recommendations that influence hardware roadmaps, launch decisions, quality plans, firmware priorities, warranty strategy, and member experience.
• Take end-to-end ownership of ambiguous, cross-functional problems and improve data science practices through documentation, peer review, reusable tooling, and mentorship.

Benefits

• Competitive salary and equity packages
• Health, dental, and vision insurance, and mental health resources
• An Ōura Ring and employee discounts for friends and family
• 20 days of paid time off, 13 paid holidays, and 8 days of flexible wellness time off
• Paid sick leave and parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed