Job Description:
SCIB Methodology Data Analytics & Models Analyst
Country:
Spain
SCIB Models & Data is looking for a Senior Risk Modeling Analyst, based in our Boadilla del Monte office.
WHY YOU SHOULD CONSIDER THIS OPPORTUNITY
Focus on Credit Risk, Interest Rate Risk, Liquidity Risk, Operational Risk, Reputational Risk.
Analyzing and quantifying various risks is essential for our goal of being a Simple, Personal, and Fair bank. Working on risks from a management perspective contributes to the sustainable progress of people and companies.
Santander values equal opportunities regardless of gender identity, culture, or disability. Our mission is to help more people and businesses prosper.
WHAT YOU WILL BE DOING
As a Senior Risk Modeling Analyst, you will develop risk measurement, capital, and forecasting models for Santander’s Corporate and Investment Banking businesses.
Responsibilities include:
* Supporting the development and maintenance of Credit Risk capital and forecasting models for Santander’s CIB portfolios (Large Corporates, Project Finance, Banks, Insurance Companies, etc.)
* Collaborating with risk and business teams to develop modeling solutions and perform ad-hoc analyses to drive new initiatives, improve processes, and deliver value through data-driven decisions.
* Designing, developing, and maintaining code for data engineering and data science tasks, mainly using Python, SQL, R, or SAS, to manipulate and analyze large datasets.
* Preparing materials for presentations, reports, or business cases for senior management, stakeholders, and regulators as needed.
EXPERIENCE AND EDUCATION
* Minimum 5 years of experience in Credit Risk Model development or related roles.
* Degree in Statistics, Mathematics, Actuarial Science, Engineering, Physics, or a similar quantitative field with a record of academic excellence.
SKILLS & KNOWLEDGE
* Proficiency in Python (mandatory), R, SQL, or SAS, and familiarity with Microsoft Office tools.
* Excellent communication skills to effectively present findings to audiences with varying technical backgrounds.
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