Credit Risk Modeler

Discover your potential during this Data Analytics Early Career Program at Rabobank.

How will you help Rabobank make better credit risk decisions through data, analytics and modelling?

You and your role

Can you connect data, modelling and business reality to create meaningful insights?

As Modelling Early Career Professional, you will turn data into meaningful models and insights that help Rabobank make better risk decisions. You will work within tribe Credit Analytics in a team of experienced modelling professionals, supporting the development, monitoring and maintenance of risk models, specifically A-IRB models and IFRS9 models for PD, LGD and EAD, as well as Early Warning Signals Models (EWS). The work is fast paced, offers a steep learning curve and combines analytical thinking with regular stakeholder interaction. You will contribute mainly to modelling activities and the associated ad-hoc analyses required to develop new models or maintain or enhance existing models while learning from experienced colleagues.

Join a team where you can learn quickly, work on meaningful modelling challenges and grow alongside experienced professionals in a collaborative and international environment.

Anil Kumar Ravulakollu, Product Manager Rural

In short

• Support the development, enhancement and maintenance of credit risk models.
• Perform data analyses, create code solutions and document outcomes.
• Present insights and findings to stakeholders and support decision-making.

You and your future

How do you turn complex data into insights that support both business goals and regulatory requirements?

You will work on credit risk modelling for the Bank’s Rural and Corporate portfolios. You will support the development, monitoring and improvement of risk models while working closely with experienced colleagues. You will analyse data, build and improve code, document findings and present your insights to stakeholders.

After completing the programme, you will have developed strong quantitative, analytical and stakeholder management skills. You will have gained experience in a highly specialised field within banking and be ready to continue your career within Rabobank in a risk modelling role.

You will join an international team where English is the primary language. Alongside your work, you will further develop yourself through the Data Analytics Early Career Program and build a valuable network across Rabobank.

Your growth in the Data Analytics Early Career Program

The Data Analytics Early Career Program is all about your development. You will intentionally invest in discovering who you are, what drives you, and how you want to grow as a professional. You will be challenged to step outside your comfort zone and explore where your strengths truly lie, sometimes in places you did not expect yourself. Through these experiences, you will learn where you can make the greatest impact.

Every Friday, the Data Analytics community comes together at the office in an open and informal environment to share knowledge, experiences and insights, and learn with and from each other. From day one, you will build a strong and valuable network that will benefit you throughout your career.

Throughout the entire programme, you can count on intensive support from experienced colleagues. Whether you want to specialise in a specific field or explore what energises you most, your growth always comes first.

Learning from each other

Development is a top priority. Because the best way to learn is by doing, through mistakes and successes, Rabobank offers the right balance between freedom and supervision. During your Data Analytics Early Career Program, you can count on excellent supervision. You will work with experienced colleagues and have lots of contact with young professionals.

You and your talent

Do you enjoy solving complex analytical challenges and explaining your insights clearly to others?

• Master's degree in Econometrics, Quantitative Finance, Economics, Applied Mathematics, Applied Physics, Engineering or a similar quantitative field.
• Experience with Python or another programming language.
• Knowledge of SQL and data analysis.
• Strong analytical and numerical skills.
• Clear communication skills and the ability to explain complex results simply.
• Knowledge about Credit Risk Modelling is a plus.
• Curiosity, learning agility and an open attitude towards feedback and collaboration.