Full-Stack Data Scientist, Hardware Reliability (Starlink)

SpaceX
United States
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 4+ yearsEducation: bachelorsSkills: ["Analytical skills","Communication","Independent execution"]

Build production data pipelines, reliability feature/label datasets, and machine-learning models that predict hardware failures for Starlink dishes, routers, power supplies, and cables. Deploy and monitor scheduled scoring systems, integrate model outputs into internal workflows via APIs and tools, and work with engineering, production, quality, supply chain, and customer experience teams to turn analytics into design and support changes. Develop LLM-backed retrieval, tool-calling, and agentic workflows to support engineers and operators.

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FursaFursa
SpaceX
SpaceX
2 days ago

Full-Stack Data Scientist, Hardware Reliability (Starlink)

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 18 hours agoStatus: Live

Job Summary

Build production data pipelines, reliability feature/label datasets, and machine-learning models that predict hardware failures for Starlink dishes, routers, power supplies, and cables. Deploy and monitor scheduled scoring systems, integrate model outputs into internal workflows via APIs and tools, and work with engineering, production, quality, supply chain, and customer experience teams to turn analytics into design and support changes. Develop LLM-backed retrieval, tool-calling, and agentic workflows to support engineers and operators.
Location: United States
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build and maintain data pipelines, infrastructure, and software to improve Starlink customer hardware reliability.
  • •Design and operate feature, label, and scoring data for reliability models, including data quality and backfills.
  • •Train, validate, and iterate hardware failure prediction models in production line and field.
  • •Deploy and operate models in production with scheduled scoring, versioning, monitoring, and iteration based on live results.
  • •Collaborate across engineering and operations teams and build analytics tools, APIs, and applications that deliver model outputs to users.
Travel: Low travel

Key Requirements

  • •Bachelor’s degree in computer science, data science, mathematics, electrical engineering, or other STEM discipline.
  • •4+ years of professional experience in data science, machine learning, or software engineering.
  • •Strong proficiency in Python and SQL.
  • •Experience building production data pipelines and deploying machine learning models in production.
  • •Experience deploying, versioning, and monitoring ML models in production, including scheduled scoring jobs consumed by other systems.
Experience:4+ yearsMachine learningData scienceSoftware engineeringData pipelinesProduction ML
Education:Bachelor's
Skills:Analytical skillsCommunicationIndependent execution
Tech Stack:PythonSQLLLMRAGAPIsGoJavaC++C#

Eligibility

Nationality:US National

Company Brief

SpaceX
Designs, manufactures, and launches advanced rockets and spacecraft for commercial and government customers, aiming to reduce space transportation costs and enable human life on Mars through reusable launch vehicles and integrated space systems.
Industry: Aerospace Manufacturing
Company Size: Enterprise (1,001+ employees)
Growth: Established Company
Valuation: Hectocorn (USD 100B+)
Funding: Series E+
Headquarters: Hawthorne, United States
Founded: 2002
Glassdoor
Glassdoor: 4.2
WebsiteLinkedIn