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# Data Scientist

- **Company:** Descripción De La Vacante
- **Location:** Spain
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Computer Vision, Microsoft Azure, Collaborative Software, Computer Programming, Data Cleansing, Cursor (Graphical User Interface Elements), Programming Tools, Python (Programming Language), Machine Learning, Object Detection, Performance Tuning, Tensorflow, Cloud Platform System, Performance Testing, Feature Engineering, GitHub Copilot, Pytorch, Retrieval-Augmented Generation, Large Language Models, Model Validation, Generative AI, Backend, Git, Pandas, Scikit Learn, Machine Learning Operations, Software Version Control
- **Published:** August 11, 2026
- **Apply:** https://es.trabajo.org/oferta-9000-a3dc35798a9057ce4c13a9885053d579

## About the Role

Stay up to date with new AI technologies, tools, and methodologies, applying them pragmatically where they add value.Required Skills & Experience- Proven experience developing AI/ML solutions in real-world environments, beyond purely academic or research contexts.- Strong programming skills in Python.- Solid knowledge of the standard machine learning ecosystem, including libraries such as pandas, scikit-learn, PyTorch, or TensorFlow.- Experience with data exploration, data preparation, feature engineering, model training, and model evaluation.- Ability to iterate quickly on experiments and prototypes.- Experience with hyperparameter tuning, performance validation, and model improvement cycles.- Good understanding of supervised and/or unsupervised machine learning techniques.- Familiarity with collaborative software development practices.- Experience with Git and code versioning.- Ability to create reproducible notebooks, experiments, and technical documentation.- Familiarity with modern
AI-assisted development tools such as GitHub Copilot, Cursor, or LLM-based coding assistants.- Fluent English, both written and spoken.Nice-to-Have Skills- Previous experience in computer vision projects, such as image classification, object detection, anomaly detection, or image-based quality analysis.- Experience working with multidisciplinary teams involving business stakeholders, product teams, engineers, and data specialists.- Knowledge of MLOps concepts, experiment tracking, model lifecycle management, or model deployment practices.- Experience with cloud environments such as AWS, Azure, or GCP.- Familiarity with APIs, backend services, or AI solution integration into production environments.- Experience with Generative AI, LLMs, embeddings, retrieval-augmented generation, or agentic AI concepts.- Understanding of responsible AI principles, model limitations, explainability, and validation risks.- Experience working in international or multicultural environments.Ideal Candidate
ProfileWe are looking for a practical and curious Data Scientist who enjoys building AI solutions that can be applied to real business problems.The ideal candidate is not only technically strong, but also pragmatic, fast-learning, and comfortable working in changing environments. They should be able to understand a problem, explore possible AI approaches, test them quickly, evaluate results objectively, and collaborate with other teams to turn promising ideas into valuable solutions.This role is especially suited for someone who enjoys working hands-on with AI, learning new domains quickly, and contributing to solutions that combine experimentation, engineering quality, and business impact.Key Personal Attributes- Practical and solution-oriented mindset.- Genuine curiosity for AI and emerging technologies.- Strong analytical and problem-solving capabilities.- Ability to learn quickly and adapt to different tech

## Description

from data exploration and experimentation to model evaluation and solution implementation.- Build, train, evaluate, and optimize machine learning models using Python and modern ML libraries.- Perform data preparation, feature engineering, model selection, hyperparameter tuning, and performance analysis.- Translate business needs into practical AI-driven solutions in collaboration with technical and non-technical stakeholders.- Develop reproducible, maintainable, and well-documented code.- Use modern AI-assisted development tools to accelerate delivery and improve development efficiency.- Collaborate with software engineers, data engineers, product owners, and business teams to integrate AI capabilities into broader solutions.- Support the technical validation of AI approaches, including feasibility analysis, accuracy assessment, limitations, and improvement opportunities.- Contribute to best practices around experimentation, version control, model evaluation, and collaborative development.-


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