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Business Data Scientist - SupplyChain & Operations

I&F Decision Science Practitioner Team Lead/Consultant | Mid-Level | Full time
Job No. R00203821 | Multiple Locations
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🚀¿Por qué? Porque queremos que tengas la oportunidad de trabajar en proyectos que transforman profundamente cómo operan las empresas. Desde la planificación y optimización de inventarios hasta el diseño de redes logísticas inteligentes, el enfoque está en aplicar ciencia de datos, machine learning y simulación para resolver problemas complejos y generar valor tangible.

  • Si tenés experiencia gestionando áreas de la supply chain y pasión por la ciencia de datos ¡Sé parte de nuestro gran Equipo!

🚀 ¿Qué desafíos te esperan?

  • Un Data Science Consultant orientado a Supply Chain & Operations Analytics es un perfil que tiene conocimiento funcional de supply chain, tiene pensamiento analítico y conoce métodos analíticos que usa como medio para resolver distintos casos de uso de negocio.
  • El área abarca el E2E: compras, planificación, producción, almacenamiento, transporte y logística, por lo que es necesario que la persona a ocupar la posición conozca los conceptos fundacionales de la cadena para poder interactuar con distintos tipos de stakeholders de cliente.
  • Es un perfil curioso que busca la causa raíz a problemas dentro de la cadena, utiliza y propone herramientas analíticas para poder resolverlo a través de distintas técnicas: optimización, machine learning, segmentación, simulación, etc.

 ¿Qué tipo de perfil nos imaginamos?

  • Profesionales de las carreras de Ingeniería Industrial, Economía, Administración de Empresas y/o afines.
  • +2 años de experiencia laboral en cualquier área de supply chain: compras, planificación, producción, almacenamiento, transporte y logística.
  • Inglés avanzado. 
  • Orientado a datos.
  • Dominio intermedio de SQL y/o Python.
  • Dominio intermedio de herramientas de visualización como Tableau y/o PowerBI.
  • Manejo de librerías para exploración y visualización de datos tales como Matplotlib y Seaborn
  • Conocimiento intermedio del proceso de desarrollo de un modelo de principio a fin: entendimiento del problema, modelo conceptual y modelo de datos, tratamiento y limpieza, codificación de modelo/análisis, validación.

 Un súper nice to have será contar con:

  • Maestrías en Ciencias de Datos, Analytics y/o afines.
  • Liderazgo y coordinación de equipos de trabajo.
  • Experiencia en entornos cloud: AWS, GCP y/o Azure.
  • Desarrollo e implementación de soluciones analíticas

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