Ir al contenidoIr al pie de página
  • Empleos
  • Empresas
  • Sueldos
  • Para empleadores

      Impulsa tu carrera profesional

      Averigua cuánto podrías ganar, encuentra el empleo perfecto y comparte información sobre tu vida laboral y personal de forma anónima.

      employer cover photo
      employer logo
      employer logo

      Yummly

      Parte de Whirlpool Corporation

      ¿Esta es tu empresa?

      Información
      Evaluaciones
      Pago y prestaciones
      Empleos
      Entrevistas
      Entrevistas
      Búsquedas relacionadas: Evaluaciones de Yummly | Empleos en Yummly | Sueldos en Yummly | Prestaciones en Yummly
      Entrevistas en YummlyEntrevistas para el cargo de Data Scientist en YummlyEntrevista en Yummly


      Glassdoor

      • Acerca de
      • Premios
      • Blog
      • Contacto

      Empleadores

      • Cuenta de empleador gratuita
      • Centro de empleador

      Información

      • Ayuda
      • Pautas
      • Condiciones de uso
      • Privacidad y opciones de anuncios
      • No vender ni compartir mi información
      • Herramienta de autorización de cookies

      Trabaja con nosotros

      • Anunciantes
      • Oportunidades laborales
      Descargar aplicación

      • Buscar por:
      • Empresas
      • Empleos
      • Ubicaciones

      Copyright © 2008-2026. Indeed, Inc. "Glassdoor", "Worklife Pro", "Bowls" y sus logotipos son marcas comerciales registradas de Indeed, Inc.

      Empresas seguidas

      Sigue a tus empresas favoritas para estar al tanto de las últimas oportunidades y disponer de información desde adentro.

      Búsquedas de empleo

      Recibe recomendaciones y actualizaciones personalizadas al iniciar tu búsqueda.

      Entrevista para Data Scientist

      23 de may de 2018
      Candidato de entrevista anónimo
      Sin ofertas
      Experiencia negativa
      Entrevista promedio

      Solicitud

      Me postulé en línea. El proceso tomó 2 semanas. Acudí a una entrevista en Yummly

      Entrevista

      Had two phone screens and then an onsite. My interview went really well in all three stages and I could not find a reason for not providing an offer. They seem to be unclear about what specialization they want to hire for as ML, DL has a lot of domains. As a suggestion to the hiring team, Do not waste time in interviewing if your requirements are not clear.

      Preguntas de entrevista [1]

      Pregunta 1

      Tech + coding questions
      Responder pregunta
      1

      Otras evaluaciones sobre las entrevistas para el cargo de Data Scientist en Yummly

      Entrevista para Data Scientist

      16 de abr de 2018
      Candidato de entrevista anónimo
      Sin ofertas
      Experiencia positiva
      Entrevista promedio

      Solicitud

      Me postulé en línea. Acudí a una entrevista en Yummly en abr 2018

      Entrevista

      Applied online. Was contacted by Greg Druck, Chief Data Scientist, to set up a time for an interview by phone. I was asked to step through projects I had worked on at my current job, it was a pretty good conversation; Greg seemed interested, asked good questions and is kind. I assumed there would be some online coding technical screen since Greg said to make sure to be near a computer for our interview. There was, kind of. It was a Google doc, but the questions were in regards to retention metrics. Honestly this totally threw me off,of all the things I have been asked during an interview this was a first. I have never dealt with retention and have never looked into it (and to be completely honest, have no interest in it). Of course it could be argued that retention is really just a stand in for any type of metric and Greg was simply looking to see how one thinks. I really don't know. However given the emphasis put on machine learning in the job description, I was expecting something related to that. I guess it just was not meant to be, and that happens. Data science interviews are tough since it seems you could be asked almost anything.

      Preguntas de entrevista [1]

      Pregunta 1

      Come up with a retention metric given this data; data consists of users, dates, and 'events.' Given these event features, how would be figure how they correlate with our defined retention metric? (I don' think they mean literally correlate, they seemed to be going in the direction of how to manipulate the data to come up with a way of determining an event features importance, but not within the context of machine learning).
      Responder pregunta
      1