Credit Risk Data Analyst

Imagine that your data analysis truly drives the solutions that sustain our business and the products that serve our customers. Our Data Analysts have to stand out from the rest. Apart from superior code-writers (MS-SQL), we need Data Analysts who question the status quo and continue to look for better solutions.

You and your job

The work you do will impact your team and your internal and external stakeholders, and ultimately also the client servicing process and therefore the bank’s core business. Our Credit Risk Data Analysts have been able to incorporate sophisticated data sources into the latest model development projects. This directly impacts the way Rabobank actively serves its clients.

Practical Examples

• You will be pro-actively aligning regulatory data requirements and gathering proper data to enable the modelling of parameters such as Probability of Default, Loss Given Default and Exposure at Default, or typical ALM topics as prepayments or pipeline
• You will support monitoring and back-testing, regulatory tasks in regards of legacy models in production with data and expertise
• You will flag DQ issues and help support the business in the remediation of the identified historical DQ issues
• You will link in with the business on subjects such as the implementation of the automated Digital lending street, IFRS9 provisioning process or product pricing & acceptance processes

Facts & Figures

• 36 or 40 hours per week
• 43,822 Rabobank colleagues around the world

Top 5 responsibilities

• As a Data Analyst you’ll need to ensure that the data request from modellers are clearly understood, and assess from which sources the data can be derived. From there on you drive the ETL process;
• You will translate requests for data into code, combining several sources, beating data into shape. You perform a series of standard and specific DQ checks, flag DQ issues and support the remediation of data where needed; ultimately, in close cooperation with the data scientists, you’ll check whether the data sets are fit for purpose;
• Support validation processes by interacting with internal and external validators;
• Support regular updates and maintenance of model data sets;
• You’ll need to have the skills and personality to act as an advisor and lead the way for your colleagues and guide them towards the goals you have agreed to achieve.

Together we achieve more than alone

We believe in the power of diversity. Bringing together people's differences is what makes us an even better bank. So we are very curious about what you can bring to our Chapter Data Credit & ALM Models.

“As a credit risk data analyst we make sure that we really understand the needs of our stakeholders before we dive into, different databases and combine data attributes to create a proper answer. It’s really a team effort so that knowledge and experience grow within our team and even beyond. Our aim for the future is to add more (graphical) insights not only for reasons like data quality but also to explain what the data is trying to tell us.”

Randolph, Senior Credit Risk Data Analyst

Around 100 professionals in Chapter Data, Credit & ALM Models are teaming up in several area’s and squads to support Credit and ALM modelling needs of the bank. Working together is the way we work; as one creative problem solving team of experts at Rabobank. Talking of Rabobank: We are a Dutch bank that operates in 38 countries for over 9,500,000 customers. Together with these customers, our members and partners we stand side by side to create a world in which everyone has access to enough healthy food. In the Netherlands we work to create a country in which people are happy with how they live, work and do business.

You and your talent

You have a Master degree Economics, Finance, IT or quantitative field

• You have at least 3 year relevant banking experience within the financial industries sector
• You have strong analytical and conceptual skills and you have gained experience in working with large volumes of data in complex data structures (untransparent, low quality). MS SQL code is a must have, some Python is helpful too.
• Strong banking knowledge, especially of credit risk, financial markets and corporate banking products and processes, and how this is translated into data flows
• You have knowledge of data modelling methodologies and techniques for data warehouses and data marts
• Strong communication skills in English, both spoken and written

This is what we offer you

• A gross annual salary between €3424,- and 6741,- per month based on 36 hours per week. Scale 8, 9 and 10 apply (depending on your experience and seniority) potentially also scale 11 could be a growth opportunity;
• thirteenth month's salary and 8% holiday allowance
• an extra budget of 10% or 11% (depending on scale) of your gross salary to be used at your discretion. Buy extra holiday hours, add more to your pension savings or ask for part of the extra budget to be paid out
• a pension scheme to which you contribute 3.5%

This is a selection of the terms of employment for a Data Analyst based on a 36-hour working week (40 hour contract is possible too).