Head of Applied Science, Growth AI for Advertising

Amazon Inc.

Seattle (WA)

Presencial

USD 219.000 - 296.000

Jornada completa

Hace 8 días

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Descripción de la vacante

Amazon.com Services LLC is seeking an experienced science leader to build and guide a team of applied scientists focused on advertiser growth, delivering personalized recommendations that help brands grow. You will own the multi-year roadmap and collaborate with product and engineering.

You will hire and develop top talent, set high scientific standards, and translate research into production-quality models that inform business decisions across teams.

Formación

  • 10+ years applying ML to large-scale problems
  • Experience distilling customer requirements into problem definitions
  • Experience hiring and developing scientists and mentoring junior members
  • Experience setting science strategy across multiple teams
  • PhD or Master's in CS, ML, or related field, or equivalent applied research

Responsabilidades

  • Set the long-term scientific vision for modeling advertiser growth journeys
  • Guide the integration of signals into personalized recommendations
  • Hire, coach, and develop scientists and engineers
  • Partner with product and engineering to productionize models
  • Set quality standards and make critical trade-off decisions

Conocimientos

ML for large-scale problems
Lead and mentor scientists
Define research direction
Cross-functional collaboration
Python & ML frameworks

Educación

PhD or Master's in CS/ML

Herramientas

Python
TensorFlow
PyTorch

Descripción del empleo

Amazon.com Services LLC is seeking an experienced science leader to build and guide a team of applied scientists focused on advertiser growth, delivering personalized recommendations that help brands grow. You will own the multi-year roadmap and collaborate with product and engineering.

You will hire and develop top talent, set high scientific standards, and translate research into production-quality models that inform business decisions across teams.

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