Senior Strategy & Market Intelligence

Requirements

• Degree in Engineering, Data Science, Statistics, or a similar quantitative field, with hands-on experience processing data. Economics or Business Administration profiles with strong data skills are also welcome.
• Three or more years of relevant experience in research, market intelligence, or data analysis, ideally in real estate or a related sector.
• Hands-on experience using AI and evolving technology to build research, not just to automate it: large language models, prompting, and workflow design applied to new analytical products. This is a core requirement, not a nice-to-have.
• Strong computational and learning ability. Technology moves fast, and we expect you to show how you have grown with it: new tools you have adopted, models you have built, and how your work has evolved as a result.
• Applied AI and analytics: working knowledge of machine-learning techniques (for example forecasting and time-series methods) and comfort building generative-AI workflows such as retrieval-augmented generation (RAG) and LLM-based extraction from unstructured documents.
• Data handling at scale: experience preparing and working with structured and unstructured big data, with SQL and at least one language for analysis or automation (Python preferred; Power Query or Alteryx also valued). Equally important, the judgment to interpret the market and translate the numbers into real-world implications.
• Track record of building and maintaining proprietary databases, market models, or analytical tools that others rely on.
• Advanced Excel and PowerPoint, plus experience with data-visualization tools (for example Power BI or Tableau).
• Knowledge of public data sources (INE, Bank of Spain, Eurostat) and real estate data platforms.
• A responsible, cost-aware approach to AI (data quality, model choice, and validation of outputs).
• Fluent English, spoken and written (minimum C1).

Competencies

• Strategic thinking: you see the market from a distinct position and you say what you see.
• Strong analytical skills and genuine interest in turning data into valuable, innovative output.
• A builder's mindset toward AI: curious, practical, and quick to test and adopt new tools.
• Business acumen: you can turn a vague question into a clear analytical objective and a plan.
• Leadership and the ability to set direction, mentor, and work across teams.
• Attention to detail and an organized, thorough approach.
• Clear communication: you can defend an analytical choice to a senior audience in plain language.
• Initiative, proactivity, and the ability to work both independently and in a team.