Descripción de la vacante
Capitole
Spain
Machine Learning Engineer en Galicia, España is listed on Jobeax. Browse 80,000+ vacancies available.
Buscamos un/a Data Scientist / ML Engineer con sólida experiencia en IA tradicional para incorporarse a un equipo de datos en expansión. La persona seleccionada será responsable de diseñar, entrenar y poner en producción modelos predictivos orientados a pricing dinámico, personalización de oferta y forecast de demanda en entornos retail de alto volumen.
El rol requiere dominio del ciclo completo de un modelo : desde el análisis exploratorio y la ingeniería de features hasta el despliegue en producción mediante pipelines de CI/CD, garantizando que los outputs lleguen a los sistemas de negocio en tiempo y forma.
Responsabilidades principales:
● Diseño y entrenamiento de modelos de regresión para forecast de demanda y elasticidad de precio .
● Desarrollo de clasificadores (churn, propensión a compra, detección de anomalías en stock).
● Construcción de sistemas de recomendación (collaborative filtering, content-based, híbridos) para personalización de oferta SKU-cliente.
● Gestión del ciclo de vida de modelos : versionado, retraining periódico y monitorización de drift.
● Integración en pipelines de CI/CD (GitHub Actions, GitLab CI o similar): testing, validación automática y promoción a producción.
● Monitorización de métricas de negocio y métricas técnicas (RMSE, AUC, ) post-despliegue.
● Traducción de requisitos de negocio (pricing managers, category managers) en problemas formales de ML.
● Documentación clara de metodología, decisiones de modelado y resultados para audiencias técnicas y no técnicas.
● Participación en code reviews y en la definición de estándares del equipo de datos.
Requisitos imprescindibles:
● 5+ años de experiencia en roles de Data Science o ML en entornos productivos.
● Dominio de Python científico (pandas, scikit-learn, numpy). SQL avanzado .
● Modelos: Regresión (lineal, Ridge, Lasso, XGBoost/LightGBM), clasificadores (RF, GBM, logística), sistemas de recomendación .
● CI/CD: Conocimiento general de pipelines de integración continua; experiencia empaquetando modelos con Docker y desplegando vía GitHub Actions, GitLab CI o similar.
● Experiencia con herramientas de tracking de experimentos : MLflow, W&B o similar.
● Capacidad de comunicar resultados de modelos a stakeholders no técnicos
Valorables:
● Experiencia en retail , travel , e-commerce o industrias con pricing dinámico .
● Conocimiento de frameworks de orquestación de datos (Airflow, Prefect).
● Familiaridad con plataformas cloud : GCP (BigQuery, Vertex AI), AWS (SageMaker) o Azure ML.
● Experiencia con feature stores (Feast, Tecton) o arquitecturas de datos en tiempo real (Kafka, Flink).
● Conocimientos de A/B testing y experimentación online para validación de modelos en producción.
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