Data Scientist, Predictive Modeling in Credit Risk - SCF HQ

Santander; Boadilla del Monte; Presencial; EUR 45.000 - 70.000; Jornada completa

Descripción de la vacante

A financial services company based in Madrid is seeking a Data Scientist specializing in Predictive Modeling within Credit Risk. This role involves developing and maintaining credit risk models, analyzing their performance, and ensuring compliance with internal and regulatory standards. The ideal candidate will possess a strong quantitative background, expertise in programming languages such as SAS and Python, and experience in data science and risk modeling.

Formación

• Years of experience in modelling in finance or related fields.
• Background in Data Science and Big Data.

Responsabilidades

• Develop, monitor, and maintain credit risk models.
• Analyze and report on risk model performance.
• Ensure adequate maintenance of risk models.
• Participate in governance processes and projects.

Conocimientos

Fluent English

Programming skills (SAS, Python, R)

Project management skills (PMI, Agile)

Team work

Ability to work in multicultural environments

Educación

Quantitative education (Engineering, Physics, Maths, Statistics)

Master in Finance or related fields

Descripción del empleo

Data Scientist, Predictive Modeling in Credit Risk - SCF HQCountry : Spain

SCF Headquarters Models is looking for a Data Scientist, Predictive Modelling and Statistics in Credit Risk based in our European offices (Madrid based).

Why you should consider this opportunity

At Santander () we are key players in the transformation of the financial sector. Do you want to join us?

Santander Consumer Finance focuses on business development related to consumer finance products, sales channels and commercial agreements with dealers, vehicle manufacturers or retail distribution establishments, as well as commercial functions associated with direct sales (branches, call centers or digital channels) and indirect sales (through third parties) of consumer finance products.

Santander is proud of being an organization where there are equal opportunities regardless of gender identity, culture and disability. Our mission is to contribute to help more people and business prosper.

What you will be doing

As a Data Scientist, Predictive Modelling and Statistics in Credit Risk you will develop, monitor and maintain models, with a first focus in Credit Risk models in Santander Consumer Finance.

We need someone like you to help us in different fronts:

• Development of risk models (admission, behaviour, fraud, propensity / affordability, stress, capital, provisions, residual value, etc.) : plan and execute models workplans agreed with different sponsors; develop models according to internal standards and guidelines, different sponsors needs and regulatory requirements, subject to data availability and data Quality; document and deliver the materials according to internal Group / local standards; support / participate during implementation phase (pre-production, allocation, etc.); securitization processes support; etc.
• Monitoring of risk models performance and report : execute and / or support the execution of monitoring reports; analyze the results of the monitoring on a proper and timely manner, proposing the actions which are needed in each case.
• Maintenance of Risk models : assure an adequate maintenance of models in force executing the actions which are needed in each case (recalibrate, adjust, time window updates, etc.) according to the results of the models monitoring, internal standards and different sponsor’s needs.
• Governance of risk models : accompany the governance processes and supervisory exercises (Internal Validation, Internal Audit, ECB / NCAs), assuring that the recommendations / obligations related to the development and maintenance of models are met on a proper and timely manner.
• Transformation and evolution projects : participate and / or sponsor local and global projects related to the digital transformation strategy in SCF (Data as a Service, migrations to new platforms, bottom-up approaches in stress models, industrialization / automation, etc.).
• Adaptation of standards and guidelines to SCF idiosyncrasy and propose new ones for digital approaches.

Experience

• years of experience in modelling in Finance field or similar needed; Data Science / Big Data needed; Credit Risk, Operational Risk and Market / ALM knowledge valuable; expected loss valuable.

Education

Quantitative education oriented (Engineering, degree Physics / Maths / Programming / Statistics / Economics / Insurance), master in Finance, Quantitative Finance, Data Science / Big Data / Machine Learning / Artificial Intelligence / Digital Transformation

Skills & Knowledge

Fluent English (C), spoken and written; high level of programming skills in different languages (SAS, Python, R, Others); project management skills valuable (PMI, Agile, etc); team work; multicultural environments