Our partner is looking for a Staff Data Scientist based in Spain.
This is a high-impact opportunity for a senior data science professional to help shape the future of statistical modeling and machine learning in residential real estate valuation.
The focus is on interpretable machine learning, statistical modeling, optimization, uncertainty estimation, and reliable production systems rather than deep learning or LLM research.
As the Data Science organization grows, you will also help establish technical standards, mentor future team members, and influence its long-term direction.
This role is adecuado for a technically strong, curious problem solver who enjoys turning novel analytical ideas into trusted software.
Design, develop, and implement production-quality statistical and machine learning systems for residential property valuation and related analytical applications.
Translate research concepts and analytical ideas into scalable, maintainable, production-ready software.
Design rigorous evaluation frameworks to measure model performance, reliability, accuracy, and robustness,



and continuously improve analytical outcomes.
Build interpretable machine learning systems that provide transparent and defensible results for consumers and professional users.
Collaborate closely with software engineering teams to integrate new analytical capabilities into production systems.
Improve the reliability, maintainability, testing, and overall engineering quality of the machine learning platform.
Establish technical standards, modeling practices, and engineering best practices for the Data Science function.
Contribute to technical hiring, mentoring, knowledge sharing, and the development of future Data Science team members.
Help shape the long-term technical direction and capabilities of the growing Data Science organization.
Strong professional background in machine learning and statistics, with experience applying advanced analytical techniques to complex business or technical p

📌 Staff Data Scientist (Madrid)
🏢 Jobgether
📍 Madrid