Scientist Responsible AI

Scientist Responsible AI - CDAIO Country Spain Job Description IT STARTS HERE Santander (www.santander.com) is evolving from a high-impact global brand to a technology-driven organization and our people are at the heart of this journey. Together we are driving a customer-centric transformation that values bold thinking innovation and the courage to challenge whats possible. This is more than a strategic shift. Its an opportunity for motivated professionals to grow learn and make a real difference. Our mission is to help people and businesses thrive. As part of the global AI Transformation team youll lead and manage strategic AI initiatives that drive impact across global companies and key functions. We are looking for someone who connects business AI and technology ensuring that AI solutions create measurable value. THE DIFFERENCE YOU MAKE Santanders Data AI Science (DAISci) team is the scientific engine of the banks AI transformation. We develop test validate and translate emerging AI methods into products that redefine how the bank learns decides and serves customers. DAISci operates at the intersection of advanced research and real-world impact - translating frontier AI into robust compliant and production-ready systems across risk customer experience operations and beyond. Joining DAISci is a rare opportunity to apply state-of-the-art AI in one of the worlds largest financial institutions shaping intelligent systems that are not only powerful but also trusted transparent and aligned with societal expectations. This role will act as a key catalyst ensuring that AI is used responsibly safely and aligned with corporate standards. Main Responsibilities We are seeking an AI SCIENTIST specializing in RESPONSIBLE AI. You will contribute to the development and operationalization of Santanders AI principles working across the different areas of the DAISci group to ensure we build safe trusted and responsible AI throughout the full lifecycle of our products - from design to deployment and monitoring. The role combines scientific research with applied execution advancing responsible AI methodologies interpretability techniques robust frameworks and alignment strategies while translating them into scalable fair and reliable systems. You will collaborate closely with engineering validation governance and product teams contribute to Santanders research and publication agenda explore emerging approaches in trustworthy AI and mentor peers to strengthen the organizations expertise in responsible and reliable AI systems. WHAT YOULL BRING TO THE TABLE Education - Advanced degree (PhD or MSc) in Computer Science Artificial Intelligence Mathematics Statistics or a related field with specialization in Responsible AI trustworthy machine learning AI safety fairness interpretability or AI governance. (Required). Professional Experience - Proven track record of advancing AI/ML through high-impact research publications patents open-source contributions or transformative product innovations - particularly in areas related to model robustness fairness explainability privacy or safety. (Required). - Demonstrated ability to translate research into production operationalizing concepts such as bias detection and mitigation interpretability techniques (e.g. SHAP counterfactuals causal methods) robustness testing model monitoring uncertainty estimation or safety guardrails into scalable and reliable systems. (Required). - Experience in AI red teaming including vulnerability analysis of conversational AI systems (LLMs) prompt injection jailbreaks strategies and security testing of generative AI applications.(Required). - Experience conducting benchmarking and evaluation of AI/ML models with particular focus on bias fairness and robustness assessments in both traditional ML systems and LLMs.(Required). Hard Skills - Strong programming skills in Python and familiarity with frameworks such as PyTorch TensorFlow DGL or PyG. (Required). - Deep understanding of responsible AI principles including fairness metrics model risk management explainability techniques adversarial robustness privacy-preserving methods and regulatory alignment (e.g. AI governance frameworks). (Required). - Strong connections with academia and the wider AI research community a passion for shaping the frontier of responsible AI ability to shape research agenda. (Required). Soft Skills - Ability to collaborate effectively with both technical and non-technical stakeholders. (Preferred).