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3 часа назад

Data Engineer (Aerospace)

Формат работы
onsite
Тип работы
fulltime
Грейд
junior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify RU Global, списка компаний с восточно-европейскими корнями
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Описание вакансии

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TL;DR

Data Engineer (Python/SQL): Developing metrics, tools, and ML models to assess the health of the Starlink business with an accent on customer acquisition efficiency and data-driven insights. Focus on building statistical dashboards, implementing monitoring systems, and validating forecasting models.

Location: Bastrop, TX. Must meet ITAR requirements (U.S. citizen, national, lawful permanent resident, refugee, or asylee).

Company

hirify.global is developing technologies to enable human life on Mars and operates Starlink, the world's largest satellite constellation providing broadband internet globally.

What you will do

  • Build high-visibility, statistically-based dashboards and analytics tools to identify trends in customer growth and experience.
  • Translate data insights into actionable items for business and engineering teams based on statistical evidence.
  • Develop and implement monitoring systems to quickly detect trends and regressions.
  • Collaborate with software and production teams to optimize user experience.
  • Develop and validate models to forecast customer acquisition.

Requirements

  • Bachelor’s degree in computer science, physics, mathematics, statistics, or a STEM discipline.
  • 1+ years of professional experience building solutions with Python and SQL.
  • 1+ years of professional experience with statistical modeling and machine learning algorithms.
  • Must be a U.S. citizen, national, lawful permanent resident, refugee, or asylee to conform to U.S. Government export regulations (ITAR).
  • Willingness to work extended hours and weekends as needed.

Nice to have

  • Experience building predictive models and ML pipelines (clustering, anomaly detection, survival analysis, time series).
  • Proficiency in data visualization, including geospatial data representations.
  • Background in statistics or computational physics.
  • Proven ability to drive positive outcomes in ill-defined problem spaces.

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