Data Scientist (Applied ML & Recommendations) at Lingokids

Madrid, ES

true · full_time · Visa sponsorship

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Responsibilities:
- Own and maintain the production recommendation infrastructure: ensure low latency, reliability and scalability for millions of users.
- Research and prototype advanced recommendation approaches (deep models, contextual bandits, session/graph methods) and evaluate uplift via experiments.
- Productionize models and features: build pipelines, CI/CD, monitoring and automated retraining to keep models healthy in production.
- Design serving and pipeline architectures to handle larger catalogs, segmentations and traffic (caching, sharding, serving optimizations).
- Build and maintain ETL/DBT/Databricks pipelines to ensure data quality and robust experimentation inputs.
- Collaborate with data scientists, product and ML engineers to integrate validated models into the live recommendation system.

Requirements:
- Strong Python and SQL skills and hands-on experience deploying ML models (AWS/SageMaker or similar).
- Proven experience with recommendation systems and production ML engineering.
- Familiarity with data pipeline tools (DBT, Databricks, Airflow/Prefect/Dagster) and CI/CD for ML.
- Experience implementing monitoring, model drift detection and operational alerting for ML services.
- Good system-design sense for scalability, latency and maintainability of ML services.
- Strong collaboration skills to work with product, experimentation and engineering teams.