BBVA (Banco Bilbao Vizcaya Argentaria) is a leading global financial services group and one of the largest financial institutions in the world, with a significant presence in Spain, Mexico, South America, and Turkey. The bank is widely recognized for its pioneering digital transformation, consistently ranking as a global leader in mobile banking and fintech innovation while managing over 120,000 employees worldwide. Headquartered in Madrid, BBVA is a major employer for international professionals, particularly within its Corporate & Investment Banking (CIB) and Engineering & Data divisions. The company operates out of 'Ciudad BBVA,' a massive, modern campus designed for agile collaboration, and offers a multicultural environment where English is the primary language for many global and technical functions.

BBVA was formed in 1999 through the merger of Banco Bilbao Vizcaya and Argentaria, though its roots date back to 1857 with the founding of Banco de Bilbao. It has evolved from a local Spanish bank into a global financial powerhouse and a digital banking pioneer.

Associate Data Scientist - Low Default Portfolios Models

BBVA

Original Advert

Excited to grow your career?

BBVA is a global company with more than 160 years of history that operates in more than 25 countries where we serve more than 80 million customers. We are more than 121,000 professionals working in multidisciplinary teams with profiles as diverse as financiers, legal experts, data scientists, developers, engineers and designers.

Learn more about the area:

The CIB Credit COE is responsible for the development, implementation and maintenance of advanced CIB credit risk models, with a particular focus on Low Default Portfolios (LDP). The area combines quantitative modelling, advanced analytics and artificial intelligence capabilities to enhance risk measurement, decision-making and capital optimization.

About the job:

We are seeking a motivated Associate Data Scientist to support the development, maintenance and enhancement of credit risk models for Low Default Portfolios (LDP). The role is suited for professionals with solid quantitative foundations who are looking to grow their expertise in credit risk modelling within an IRB framework, working closely with senior modelers and business stakeholders.

The position focuses on contributing to the development of PD, LGD and CCF models, data analysis, and model implementation for LDP portfolios across different asset classes.

Responsibilities:

Support the development and maintenance of credit risk models and parameters (PD, LGD, CCF) for Low Default Portfolios.
Perform data analysis, feature engineering and exploratory studies to support model development and calibration.
Contribute to model estimation, testing, backtesting and performance monitoring activities.
Assist in the integration of internal and external data sources into modelling frameworks.
Support the documentation of models and methodologies in line with internal governance and regulatory requirements.
Collaborate with senior data scientists, risk managers and technology teams in the implementation of models into production.
Participate in interactions related to model reviews, validations and regulatory processes.

Qualifications:

2-5 years of experience in analytical or quantitative roles, preferably within the financial sector.
Academic background in Mathematics, Statistics, Engineering, Economics, Physics or related quantitative fields.
Exposure to credit risk modelling or risk analytics, ideally within Low Default or corporate portfolios.
Basic knowledge of IRB approaches and regulatory frameworks for credit risk (Basel).
Proficiency in Python (or similar statistical/programming tools) for data analysis and modelling.
Strong analytical skills and attention to detail, with the ability to work with complex datasets.
Willingness to learn and grow in a highly technical and regulated environment.
Good communication skills and ability to work collaboratively in multidisciplinary teams.
Fluent in English.

Skills: