Data Scientist - NLP
Electronic Arts
Description & Requirements
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
- Analyze large, multilingual datasets to generate actionable insights for localization workflows.
- Design and build ML and DL models for Natural Language Processing (NLP), Computer Vision, and other localization-related tasks.
- Develop and refine feature engineering pipelines tailored for multilingual and multimodal datasets.
- Evaluate model performance, conduct error analysis, and iterate to improve accuracy, fairness, and reliability.
- Apply statistical analysis, A/B testing, and experimental design to evaluate the impact of localization strategies.
- Contribute to the deployment and monitoring of models in production in partnership with ML Engineers, ensuring scalability and maintainability.
- Use tools like MLflow, Vertex AI, or Sagemaker for conducting and tracking experiments and managing model lifecycles.
- Conduct code reviews and ensure high-quality coding standards.
- Ensure adherence to ethical AI standards.
- 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 ( Moisés Martinez AÑADE LISTA) 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.