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Sr. Validation Data Scientist

Job in Irvine, Orange County, California, 92713, USA
Listing for: Rivian
Full Time position
Listed on 2026-05-21
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Data Engineering, Data Scientist
Salary/Wage Range or Industry Benchmark: 135100 - 168900 USD Yearly USD 135100.00 168900.00 YEAR
Job Description & How to Apply Below

About Rivian

Rivian is on a mission to keep the world adventurous forever. This goes for the emissions‑free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.

As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.

Role Summary

Vehicle Validation at Rivian ensures every product delivers exceptional function, quality, reliability, and real‑world performance. We perform both verification and validation against data‑driven requirements that reflect how our customers use our vehicles—leveraging scalable analytics, integrated data pipelines, and validation governance frameworks to continuously improve how we plan, execute, and learn.

As a Senior Data Scientist, Vehicle Validation, you will develop and scale data products, analytics frameworks, and modeling approaches that enable visibility into validation coverage, risk, and readiness from concept through launch and into early field performance.

You will partner closely with Validation TPMs, Engineering, Quality, Test & Development, and Data Engineering to transform fragmented validation data into clear, actionable insights—helping ensure the right tests happen at the right time and that leadership has a clear view of validation status and risk.

This is a RIV-5 scope role: you will own key analytics work streams within the validation data ecosystem, operating with guidance from validation and technical leadership while building toward greater end‑to‑end ownership over time.

Responsibilities
  • Develop and maintain validation dashboards, analytics, and reporting that provide visibility into validation coverage, maturity, risk, and residuals across programs.
  • Build and support data models that connect requirements (RL0–RL3), DFMEA / NUDDs, DVPs, test execution, and issue tracking into a cohesive validation data framework.
  • Create and maintain data pipelines that ingest and structure data from systems such as Jira, test logs, vehicle telemetry, and other internal tools.
  • Apply statistical and machine learning techniques (e.g., trend analysis, forecasting, anomaly detection) to identify risks, gaps, and opportunities within validation data.
  • Partner with Validation TPMs and cross‑functional teams to translate data into actionable insights that support program execution and decision making.
  • Support the definition and tracking of validation KPIs (e.g., coverage, confidence, defect trends, closure rates, readiness metrics).
  • Contribute to validation governance by enabling consistent, reliable, and accessible data across builds and milestones (DV → PV → SOP+).
  • Identify data gaps or inconsistencies and work with stakeholders to improve data quality, structure, and usability.
  • Contribute to continuous improvement of validation data infrastructure, tools, and processes to increase efficiency and scalability.
Qualifications
  • Typically 3–6 years of experience in data science, analytics, or related roles within automotive or other complex hardware/software products.
  • Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, or a related technical field.
  • Experience building data pipelines and analytics solutions (e.g., Python, SQL, and cloud platforms such as AWS or GCP).
  • Experience developing dashboards and visualizations (e.g., Hex, or similar) to support operational decision making.
  • Experience working with large, multi‑source datasets and building structured data models.
  • Familiarity with machine learning techniques and their practical application to real‑world problems.
  • Strong collaboration and communication skills, with the ability to work across technical and non‑technical teams.
  • Comfortable working in ambiguous environments with a willingness to learn new domains and systems quickly.
  • Passion for improving product quality, reliability, and customer experience through data.
Pay Disclosure

The salary range for this role is $135,100 - $168,900 for California…

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