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Machine Learning Automation Lead

hace 3 meses

Madrid, Madrid, España MAPFRE A tiempo completo
Misión Garantizar que el Machine Learning y otros modelos avanzados de IA son implementados con éxito y gobernados para garantizar los entregables esperados. Proporcionar soporte tecnológico experto y asesorar a los Business Data Scientist y garantizar la coordinación con el equipo de Data Engineering y otros equipos de TI para operacionalizar los modelos de Machine Learning e Inteligencia Artificial. Actuar como Centro de Excelencia para orientar a las entidades con menor nível de madurez.- Funciones- Diseño, desarrollo e investigación sobre sistemas de Machine Learning, modelos y esquemas.

  • Estudiar, transformar, y convertir prototipos de Data Science.
  • Buscar y seleccionar Data Sets apropiados.
  • Desempeñar análisis estadísticos y utilizar sus resultados para mejorar los modelos.
  • Garantizar el entrenamiento y reentrenamiento de Sistemas y Modelos de Machine Learning cuando sea necesario.
  • Identificar diferencias en la distribución del dato de modo que pueda afectar al desempeño / calidad de los modelos en producción.
  • Uso de técnicas de Visualización del dato para análisis más complejas.
  • Analizar los casos de uso de los Algoritmos de Machine Learning, y priorizar los que tengan mayor probabilidad de éxito.
  • Identificar insights (extrair conocimiento de los datos) que puedan ser aplicados a decisiones de negocio.
  • Enriquecimiento de los Frameworks y Librerías de Machine Learning.
  • Validación de la calidad del dato, garantizándolo mediante técnicas de Data Cleaning.
  • Evolucionar el framework de ML OPS a nível de tecnología, procesos y Best Practices.
  • Desarrollar programas de aprendizaje en técnicas de Machine Learning.
  • Ayuda en el escalado y la reutilización de productos Datos de Machine Learning, así como en la operacionalización de dichos entregables en distintas entidades.


 Requisitos
  • Titulación Universitaria Superior (Ingeniería Informática, Telecomunicaciones o similar).
  • Nível mínimo requerido C1 de Inglés
  • Conocimientos sólidos en Matemáticas, Estadística, e Ingeniería del Software.
  • Conocimiento en la aplicación de aprendizajes supervisados y no supervisados (Deep learning, regresiones, clasificación, clustering, detección de anomalías, sistemas de recomendación, Programación de Lenguaje Natural)
  • Experiência solvente en lenguajes de programación para analítica (R, Python, Spark) y herramientas de visualización (Tableau, PowerBI)
  • Conocimiento de mejores prácticas de programación (p

e:
control de versiones, desarrollo orientado a pruebas, CI/CD, etc.)

  • Conocimiento profundo de SQL, preparación de datos, técnicas de Análisis Exploratória de Datos.
  • Conocimiento asentado en Modelos de Monitorización de Machine Learning, y en la evaluación y operacionalización de modelos (MLOps)


 Competencias
  • Orientación al Cliente
  • Alta capacidad de comunicación e interlocución
  • Innovación
  • Pensamiento analítico
  • Iniciativa y trabajo en equipo.