About the role
As a Senior Data Scientist – Applied AI, you’ll take complex problems from exploration and experimentation through to production. You’ll work across machine learning, NLP and generative AI, selecting and evaluating the right approaches to build effective, reliable solutions.
You’ll bring strong Python and data science skills alongside hands-on experience with modern AI, including LLMs, retrieval and agents. You’ll also work closely with ML and Infrastructure Engineers to ensure the solutions you build are reliable, scalable and maintainable in production.
As a senior member of the team, you’ll be expected to make sound technical decisions, challenge assumptions, support other Data Scientists and help shape the approaches and technologies we adopt.
We also care deeply about responsible AI. You’ll consider privacy, security, provenance, model limitations and appropriate human oversight as part of how solutions are designed and built.
What you’ll be doing
Lead data science and applied AI work from exploration and experimentation through to production
Develop and evaluate machine learning, NLP and generative AI solutions, selecting the approach that best fits the problem
Build applications using LLMs and techniques such as structured generation, embeddings, semantic search, retrieval, RAG, tool use and agents
Develop production-quality Python services, APIs and data pipelines that integrate models and AI capabilities into real products and workflows
Design experiments and evaluation frameworks to compare approaches, measure quality and understand where systems succeed and fail
Work with structured and unstructured data at scale using SQL and modern data platforms
Collaborate with ML and Infrastructure Engineers on deployment, containerization, monitoring and production operations
Work directly with colleagues across the business to turn open-ended questions into practical technical solutions
Support other Data Scientists and contribute to shared technical standards, reusable components and best practices
Collaborate with Data Science & AI colleagues globally, while staying current with developments in machine learning and AI and helping identify which new approaches are worth adopting
What you’ll bring
Essential
5+ years of professional experience in data science, machine learning, applied AI or a related technical discipline
Advanced Python skills and the software engineering practices needed to build maintainable production code
Strong foundations in machine learning and data science, including model development, experimentation and evaluation
Practical experience building with large language models and generative AI
Understanding of modern LLM application patterns, including prompting, structured outputs, embeddings, retrieval/RAG and tool or function calling
Experience designing robust approaches to model evaluation and interpreting results critically
Strong SQL and experience working with substantial datasets
Experience with cloud environments and modern data platforms
Experience building or integrating APIs, services or data pipelines
The ability to move comfortably between experimentation and engineering, rather than stopping at a successful notebook or proof of concept
Strong problem-solving skills and the confidence to make technical decisions when the path isn’t obvious
The ability to communicate clearly with both technical and non-technical colleagues
A high level of professional English, as much of your collaboration will be with international teams
Nice to have
Production experience with agents or multi-step LLM systems
Experience with frameworks such as PydanticAI, DSPy, LangChain/LangGraph or provider-specific agent SDKs
Familiarity with LLM evaluation, tracing and observability tools
Experience with AWS
Experience with Snowflake and/or Databricks
Experience with Docker, Kubernetes and CI/CD
Experience building applications using FastAPI, TypeScript, React or similar technologies
Knowledge of information retrieval, semantic search and vector databases
Understanding of AI-specific security risks such as prompt injection, inappropriate tool access and data leakage
Experience mentoring other technical colleagues or contributing to technical standards
Basic or conversational Spanish
How we work
This position is based in Barcelona and follows a hybrid working model.
You’ll be part of an international team, working closely with US-based leadership and colleagues across Penguin Random House globally.
What do we offer?
A flexible working culture, with a 50% remote working model
Offices located in the city centre
Reduced working hours on Fridays, days before public holidays, and during the summer months
Company mobile phone
Access to our e-book and audiobook app
More annual leave than required under the applicable collective agreement
Meal vouchers
Discounts on company products
… And much more!
Information requirements regarding the collection of your personal data
The entity responsible for processing the information provided in your application is the company specified in the job advertisement, with its registered office at the address indicated therein. The company processes your personal data for the purpose of establishing an employment relationship, in accordance with Article 6(1)(b) of the GDPR / Section 26(1), sentence 1 of the BDSG.
The retention period for your personal data is determined by the applicable statutory retention periods in the relevant country, which begin once the recruitment process has been completed. Further information can be found here.
You may contact the company’s Data Protection Officer at the postal address mentioned above or by email.
Further information about data protection and your rights can be found here.
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Requisitos de información relativos a la recogida de sus datos personales:
La entidad responsable del tratamiento de la información facilitada en su solicitud es la empresa indicada en la oferta de empleo, con domicilio social en la dirección indicada. La empresa trata sus datos con el fin de establecer una relación laboral, de conformidad con el artículo 6, apartado 1, letra b) del RGPD / artículo 26, apartado 1, frase 1 de la BDSG.
El plazo de conservación de sus datos viene determinado por los plazos legales aplicables en el país correspondiente, que comienzan una vez finalizado el proceso de selección. Puede consultarlos aquí.
Puede ponerse en contacto con el delegado de protección de datos de la empresa en la dirección postal mencionada anteriormente o por correo electrónico.
Puede encontrar más información sobre la protección de datos y sus derechos aquí. Requisitos de información relativos a la recogida de sus datos personales.
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