Senior Data Scientist – Cyber Risk Analytics

Description

You would join the Security Analytics team, focused on managing cyber risk from third-party vendors, in a new Senior Data Scientist role.

The company is setting up a new hub in Spain, its sixth worldwide, to design and deliver technology and operations solutions for customers. It will join a network of over 13,000 professionals across the Philippines, Poland, Romania, Slovakia, Türkiye and Spain.

The company serves more than 34 million customers in over 38 countries and aims to become Europe's best bank.

Responsibilities

• Build and run AI and machine learning models that measure, assess and track cyber risk from third-party vendors.
• Early on, you will build continuous risk models and dynamic vendor scores, replacing periodic reviews with a more proactive, data-led approach.
• Create dynamic vendor risk scores by combining internal and external sources such as risk assessments, security posture indicators and threat intelligence.
• Apply predictive analytics, anomaly detection and other advanced techniques to identify and rank risks more accurately.
• Explore agentic AI solutions built on large language models, tool integration and automated reasoning to support risk assessment, intelligence gathering and decision-making.
• Own the full model lifecycle: data preparation, feature engineering, development, validation, deployment, monitoring and recalibration.
• Work with TPCRM specialists, cybersecurity teams and data engineers to turn complex risk problems into scalable solutions.
• Make sure models are robust, explainable and consistent with internal model governance, data quality and regulatory requirements.
• Explain findings, model performance and risk insights to both technical and non-technical audiences.
• Look for new data science use cases that strengthen third-party cyber risk management.

Requirements

• A master's degree or PhD in data science, computer science, statistics, mathematics, physics or a related quantitative field.
• 7+ years of professional experience in data science, advanced analytics, statistical modelling or machine learning, preferably including solutions taken into production.
• Familiarity with generative AI, LLM-based applications and emerging agentic AI architectures, including their practical uses and limits.
• Strong Python and SQL skills, with hands-on use of common data science and machine learning libraries.
• A proven record of developing, validating and maintaining statistical and machine learning models across their lifecycle.
• A solid grasp of statistical methods, predictive modelling, feature engineering, model evaluation and uncertainty.
• Experience with complex, heterogeneous data and turning vague business problems into structured analytical approaches.
• Familiarity with model deployment, monitoring, reproducibility and MLOps practices.
• Ability to lead technical initiatives independently while working well with multidisciplinary teams.
• Strong analytical, problem-solving and communication skills, including explaining complex modelling approaches to non-technical audiences.
• Preferred qualifications
• Experience building and deploying AI in heavily regulated settings, particularly financial services.
• Familiarity with cybersecurity, cyber risk management, third-party risk management or cyber risk metrics.
• Experience with risk scoring, probabilistic modelling, 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.

Conditions

Hybrid working: you agree with the company which days you work from home and which you spend at the Madrid office.

The company is committed to diversity, inclusion and belonging.

Benefits

• Restaurant card to cover your lunch.
• Health insurance covering you plus your spouse or partner and children.
• Life insurance.
• Flexible remuneration: tax-advantaged access to services such as nursery places, transport cards and training aids.
• Transport allowance to help you get to the office, wherever you live.
• Pension plan you can join after 1 month with the company.
• Electric mobility options, a doctor, a hairdresser, a gym and a service that helps with errands, available at the office.