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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - **Company:** Clarivate Analytics - **Location:** Barcelona, Spain - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Continuous Integration, Python (Programming Language), Machine Learning, Azure Machine Learning, Software Deployment, Feature Engineering, Model Validation, Information Technology, Machine Learning Operations, Data Pipelines, Docker - **Published:** August 12, 2026 - **Apply:** https://eu.experteer.com/career/view-jobs/senior-data-scientist-08036-barcelona-cataluna-spanien-58891004 ## About the Role years and ensure seamless integration * Communicate findings clearly to technical and non-technical audiences * Promote best practices in ML, experimentation, and model evaluation Tasks * Master's degree in Computer Science, Data Science, Machine Learning, Engineering, or related field (preferred) * 5+ years of professional experience in ML/AI/NLP/data science with production deployments * 3+ years of hands-on ML lifecycle experience (data prep, feature engineering, modeling, validation, deployment, monitoring, retraining) * 5+ years of Python development experience for production-grade apps and data pipelines * 2+ years of cloud ML platforms (AWS, GCP, and/or Azure) and MLOps tools (Docker, MLflow) in enterprise environments * 3+ years in Agile software development with CI/CD and evolving requirements Key requirements * hybrid work model * flexible hours * support from a large Data Science team * mentorship and growth opportunities ## Description Experteer Overview As a Senior Data Scientist at Clarivate in Barcelona, you will build and productionize ML/AI/NLP solutions that enhance knowledge search for IP and science domains. You will work within a cross-functional Data Science, Search and Content team to turn strategic information needs into impactful AI capabilities. The role combines exploration, experimentation, and production deployment to drive measurable business impact. You will join a collaborative, mentorship-driven environment that values cutting-edge ML and ongoing learning. Pay / Benefits * Identify strategic information needs from clients and translate them into effective AI solutions * Collaborate with fellow Data Scientists to support high-stakes decision-making in researchers' workflows * Explore data sources, perform exploratory analysis, and recommend data enhancements * Design and run experiments to validate hypotheses and quantify business impact * Partner with engineering to deploy solutions into production and ensure seamless integration * Communicate findings clearly to technical and non-technical audiences * Promote best practices in ML, experimentation, and model evaluation Tasks * Master's degree in Computer Science, Data Science, Machine Learning, Engineering, or related field (preferred) * 5+ years of professional experience in ML/AI/NLP/data science with production deployments * 3+ years of hands-on ML lifecycle experience (data prep, feature engineering, modeling, validation, deployment, monitoring, retraining) * 5+ years of Python development experience for production-grade apps and data pipelines * 2+ years of cloud ML platforms (AWS, GCP, and/or Azure) and MLOps tools (Docker, MLflow) in enterprise environments * 3+ years in Agile software development with CI/CD and evolving requirements Key requirements * hybrid work model * flexible hours * support from a large Data Science team * mentorship and growth opportunities ## Related Videos - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Implementing continuous delivery in a data processing pipeline](https://www.wearedevelopers.com/videos/73-implementing-continuous-delivery-in-a-data-processing-pipeline) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)