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Artificial Intelligence Lead - Insurance DomainSantander · Madrid
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Santander

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Artificial Intelligence Lead - Insurance Domain

🗓️ Posted 2026-09-23 Madrid Hybrid ICT
💰 Salary Not shared 📊 Market 4,500 EUR–6,500 EUR/mo

About the Company

race a strong risk culture and all our professionals at all levels are expected to take a proactive and responsible approach toward risk management. The Wealth Management & Insurance division covers three businesses in all Santander Group countries: Insurance, Asset Management and Private Banking. We work to provide the best solutions to our clients in these three businesses in the 10 countries where we are present. THE DIFFERENCE YOU MAKE Santander Insurance is looking for an Artificial Intelligence Lead based out of Madrid . As an Artificial Intelligence Lead for the Insurance Domain , you will drive the strategic development and implementation of AI technologies across insurance value chains, accelerating digital transformation, enhancing risk assessment capabilities, improving claims efficiency, and strengthening customer engagement through advanced AI solutions.

About the Role

Data & Artificial Intelligence Office (CDAIO) and with Insurance Product, Underwriting, Claims, Pricing, Risk, Distribution, and Operations teams. This is a unique opportunity to shape the AI agenda within the Insurance business and spearhead the deployment of AI and GenAI solutions to generate competitive advantage and sustainable growth. We're shaping the way we work through innovation, cutting-edge technology, collaboration and the freedom to explore new ideas. To succeed in this role, you will be responsible for: Develop and execute a comprehensive AI strategy aligned with Insurance business objectives (growth, loss ratio optimization, customer retention, operational efficiency). Identify and prioritize high-impact AI and GenAI use cases across the insurance value chain, including: Underwriting automation and risk scoring Pricing optimization and actuarial modeling enhancement Claims automation and fraud detection Customer service virtual assistants and policy servicing Document intelligence for policy and claims processing Design and deploy AI-powered solutions to improve combined ratio, customer experience, and operational scalability. Lead cross-functional teams (Data Science, IT, Actuarial, Risk, Operations, Compliance) in AI solution design and integration. Oversee development, validation, and monitoring of machine learning models for predictive analytics and risk modeling. Ensure compliance with insurance regulatory framewor

Requirements

  • ● Our people are our greatest strength. Every individual contributes unique perspectives that make us stronger as a team and as an organization. We're enabling teams to go beyond by valuing who they are and empowering what they bring.
  • ● The following requirements represent the knowledge, skills, and abilities essential for success in this role. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
  • ● Professional Experience
  • ● Proven experience with GenAI and AI/ML applications in Insurance. (Required)
  • ● + years of experience in AI/ML roles with strong applied problem-solving background. (Required)
  • ● + years of experience in Insurance (Life, P&C, Health, or Reinsurance) or insurance technology. (Required)
  • ● Demonstrated experience implementing AI/ML solutions in underwriting, pricing, claims, fraud, or customer analytics. (Required)
  • ● Strong understanding of actuarial concepts, risk modeling, and insurance KPIs (loss ratio, combined ratio, retention, claims leakage). (Required)
  • ● BSc or MSc degree in Computer Science, Artificial Intelligence, Mathematics, Actuarial Science, Engineering, or related quantitative field. (Required)
  • ● AI/ML, cloud, or data science certifications. (Preferred)
  • ● Fluent English and Spanish (Required)
  • ● Expert-level knowledge of machine learning algorithms and predictive modeling.
  • ● Strong understanding of GenAI, LLM applications, and prompt engineering in regulated environments.
  • ● Proficiency in Python and AI development frameworks.
  • ● Knowledge of MLOps, model governance, and model risk management frameworks.
  • ● Understanding of actuarial modeling and insurance risk assessment processes.
  • ● Familiarity with insurance regulatory requirements (e.g., Solvency II, IFRS 17, local supervisory frameworks).
  • ● Strong strategic thinking and innovation leadership capabilities.
  • ● Excellent communication skills across technical and business stakeholders.
  • ● Advanced analytical and problem-solving skills.