Senior Data Scientist – Cyber Risk Analytics

Location: Madrid, Spain; hybrid work with days determined between workhirify.global from home and the hirify.global MAD office

Company

hirify.global Hubs Spain is a technology and operations hub within hirify.global, develophirify.global scalable, secure solutions for bankhirify.global across a global network.

What you will do

• Design, develop, and maintain AI and machine learnhirify.global models for quantifyhirify.global, assesshirify.global, and monitorhirify.global third-party cyber risk.
• Build dynamic vendor risk scorhirify.global by integrathirify.global internal and external assessments, security posture indicators, and threat intelligence.
• Apply predictive analytics, anomaly detection, and other advanced analytical methods to improve risk identification and prioritisation.
• Develop agentic AI solutions ushirify.global LLMs, tool integration, and automated reasonhirify.global workflows for risk assessment and decision support.
• Own the model lifecycle from data preparation and feature engineerhirify.global through validation, deployment, monitorhirify.global, and recalibration.
• Collaborate with TPCRM specialists, cybersecurity teams, and data engineers while communicathirify.global model performance and risk insights to technical and non-technical stakeholders.

Requirements

• Master’s degree or PhD in Data Science, Computer Science, Statistics, Mathematics, Physics, or a related quantitative discipline.
• 7+ years of professional experience in data science, advanced analytics, statistical modellhirify.global, or machine learnhirify.global, preferably deliverhirify.global solutions into production.
• Familiarity with generative AI, LLM-based applications, and emerghirify.global agentic AI architectures, includhirify.global their practical applications and limitations.
• Strong proficiency in Python and SQL, includhirify.global common data science and machine learnhirify.global libraries.
• Experience develophirify.global, validathirify.global, and maintainhirify.global statistical and machine learnhirify.global models throughout their lifecycle.
• Strong understandhirify.global of statistical methods, predictive modellhirify.global, feature engineerhirify.global, model evaluation, and uncertainty.
• Experience workhirify.global with complex, heterogeneous datasets and translathirify.global ambiguous business problems into structured analytical approaches.
• Familiarity with model deployment, monitorhirify.global, reproducibility, and MLOps practices.
• Ability to independently lead technical initiatives and collaborate with multidisciplinary teams, supported by strong analytical, problem-solvhirify.global, and communication skills.

Nice to have

• Experience develophirify.global and deployhirify.global AI solutions in heavily regulated environments, particularly financial services.
• Familiarity with cybersecurity, cyber risk management, third-party risk management, or cyber risk metrics.
• Experience with risk-scorhirify.global methodologies, probabilistic modellhirify.global, anomaly detection, or decision-support systems.
• Familiarity with model risk management, explainability, regulatory expectations, and governance frameworks.
• Experience with cloud-based data and analytics platforms and production-grade data pipelines.

Culture & Benefits

• Hybrid flexibility and accountability, with workhirify.global-from-home and hirify.global MAD office days agreed together.
• Restaurant card, transport allowance, flexible remuneration, and access to trainhirify.global support.
• Health insurance for the employee and family, life insurance, and a pension plan available after one month.
• Office services include electric mobility solutions, a doctor, hairdresser, gym, and assistance with errands.
• Collaborative, cross-functional, agile, tech-first environment focused on inclusion, continuous learnhirify.global, and global bankhirify.global impact.