Senior Data Scientist / AI Engineer

Description

The Data Science team builds tools that help the company make decisions that are ethical, commercially responsible and better informed.

The team blends data science, machine learning and recent AI advances to tackle real business problems and turn early ideas into tools people can use day to day.

The role is based in Barcelona and sits in a global Data Science and AI group that shares technology and practice with colleagues in the US and across the company.

The Senior Data Scientist (Applied AI) takes hard problems from early exploration all the way to production, spanning machine learning, NLP and generative AI, and chooses and tests the methods that fit.

You bring strong Python and data science skills plus practical AI experience with LLMs, retrieval and agents, and you work with ML and infrastructure engineers so solutions stay reliable, scalable and easy to maintain.

As a senior team member, you make sound technical calls, question assumptions, mentor other data scientists and help decide which approaches and technologies the team adopts.

Responsible AI matters here: privacy, security, provenance, model limits and human oversight are considered as solutions are designed and built.

Responsibilities

• Lead data science and applied AI projects from exploration through to production.
• Build and assess machine learning, NLP and generative AI solutions, picking the method that suits each problem.
• Create LLM-based applications using structured generation, embeddings, semantic search, retrieval, RAG, tool use and agents.
• Write production-grade Python services, APIs and data pipelines that connect models and AI features to real products and workflows.
• Design experiments and evaluation frameworks that compare options, measure quality and show where systems fail.
• Work with large structured and unstructured datasets using SQL and modern data platforms.
• Partner with ML and infrastructure engineers on deployment, containers, monitoring and day-to-day production operation.
• Work directly with colleagues across the business to turn open-ended questions into practical technical answers.
• Support other data scientists and contribute to shared standards, reusable components and best practices.
• Keep up with developments in ML and AI, and help judge which new approaches are worth adopting.

Requirements

• Essential: 5+ years of professional work in data science, machine learning, applied AI or a closely related technical area.
• Essential: Advanced Python and the engineering habits needed to ship maintainable production code.
• Essential: Solid grounding in machine learning and data science, covering model building, experimentation and evaluation.
• Essential: Hands-on experience building with large language models and generative AI.
• Essential: Working knowledge of LLM application patterns such as prompting, structured outputs, embeddings, retrieval/RAG and tool or function calling.
• Essential: Ability to evaluate models robustly and interpret results with a critical eye.
• Essential: Strong SQL and experience with large datasets.
• Essential: Experience with cloud environments and modern data platforms.
• Essential: Experience building or integrating APIs, services or data pipelines.
• Essential: Comfort moving between experimentation and engineering, not stopping at a working notebook or proof of concept.
• Essential: Clear problem-solving and the confidence to make technical decisions when the path is unclear.
• Essential: Clear communication with both technical and non-technical colleagues.
• Essential: Professional-level English, as most collaboration is with international teams.
• Production experience with agents or multi-step LLM systems.
• Experience with frameworks such as PydanticAI, DSPy, LangChain/LangGraph or provider 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 with FastAPI, TypeScript, React or similar.
• Knowledge of information retrieval, semantic search and vector databases.
• Understanding of AI security risks such as prompt injection, unsafe tool access and data leakage.
• Experience mentoring technical colleagues or contributing to technical standards.
• Basic or conversational Spanish.

Conditions

Based in Barcelona with a hybrid working model, including a 50% remote arrangement.

You join an international team that works closely with US-based leadership and colleagues across the company.

Offices are in the city centre.

Reduced hours on Fridays, on days before public holidays and during the summer months.

Your application data is handled by the hiring company for recruitment, and kept for the legal periods that apply in your country once the process ends.

Benefits

• Company mobile phone.
• Access to the company's e-book and audiobook app.
• More annual leave than the applicable collective agreement requires.
• Meal vouchers.
• Discounts on company products.
• Plus further perks.