Electronic Arts

We are hiring a Data Scientist to join our Localization Data & AI team, reporting to the Data Scientist Lead in our Madrid office, with required attendance 3 days a week.

The Loc Data & AI team’s mission is to empower EA Localization through intelligent, data- driven solutions leveraging advanced analytics, scalable AI systems, and collaborative tools that enhance the quality and efficiency of localized content.

As a Data Scientist in our team, you will focus on building end-to-end data science solutions from exploratory analysis to model development and performance evaluation working closely with Machine Learning Engineers and Data Engineers.

Responsibilities

1. Analyze large, multilingual datasets to generate actionable insights for localization workflows.
2. Design and build ML and DL models for Natural Language Processing (NLP), Computer Vision, and other localization-related tasks.
3. Develop and refine feature engineering pipelines tailored for multilingual and multimodal datasets.
4. Evaluate model performance, conduct error analysis, and iterate to improve accuracy, fairness, and reliability.
5. Apply statistical analysis, A/B testing, and experimental design to evaluate the impact of localization strategies.
6. Contribute to the deployment and monitoring of models in production in partnership with ML Engineers, ensuring scalability and maintainability.
7. Use tools like MLflow, Vertex AI, or Sagemaker for conducting and tracking experiments and managing model lifecycles.
8. Conduct code reviews and ensure high-quality coding standards.
9. Ensure adherence to ethical AI standards.
10. Stay up-to-date with the latest research in NLP, machine learning, and localization technologies.

Qualifications

• 3+ years of hands-on experience in applied data science, ideally in NLP, computer vision, or multilingual domains.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Maths, Statistics, Linguistics, or a related field.
• Strong proficiency in Python and core data science libraries (Pandas, NumPy, scikit-learn, Matplotlib, Seaborn).
• Experience   with   ML   and   DL   frameworks   (TensorFlow,   PyTorch,   Hugging   Face Transformers).
• Familiarity   with   cloud-based   platforms   (AWS,   GCP,   Azure)   and   tools   for   model development and deployment.
• Solid grasp of statistical methods, hypothesis testing, and experimental design.
• Familiarity with NLP concepts and tools (e.g., BLEU, BERTScore, spacy, nltk, quality estimation) is a plus.
• Familiarity with Computer Vision concepts and tools is a plus.
• Familiarity with MLOps concepts and tools (e.g., MLflow, Vertex AI) is a plus.
• Strong communication skills with the ability to convey technical insights to non-technical audiences.
• Passion for localization, culturalization, language technologies, and building AI that enhances global user experiences.