Data Analyst within COO Risk

ING is looking for a Data Analyst within COO Risk  

Are you passionate about data and ready to make an impact? ING is looking for an ambitious, enthusiastic, and driven Data Analyst to join COO Risk within The Center of Expertise Credit Risk Modelling Data. If you thrive on working with complex data and continuously seek ways to improve processes, then we are looking for you! 

The opportunity 

As a Data Analyst within Data Remediation, you will be responsible for sourcing, processing, automating, analyzing, and delivering high-quality credit data. This data is a key input for ING’s global Wholesale Bank Credit Risk models (e.g., AIRB, FIRB, Feeder, IFRS9) and supports various model lifecycle processes such as development, recalibration, and monitoring. 

Work environment 

COO Risk sits right at the heart of the Bank’s operations. We translate our rather complex banking business exposures into impact on risk weighted assets and provisions in line with the constantly changing business desires and the latest regulatory requirements. We also provide important insights in NFR and Compliance topics and cater for corresponding regulatory reporting needs. COO Risk delivers baseline and change activities for the Risk Organization with the purpose to drive our partners to maximize value in a safe & compliant environment. We play a critical role at ING and service all business lines, CROs and COOs of the Bank. COO Risk is committed to take explicit ownership of the end-to-end execution of regulatory transformation initiatives. 

The Center of Expertise Credit Risk Modelling Data is responsible for delivering model-ready credit risk data for ING's global WB Credit Risk modelling landscape. The CoE acts as a single point of contact for modelling data sets, bringing together scoping, Default and LGD data capabilities while ensuring data is sourced, processed, delivered and governed in line with ING's regulatory and modelling standards. The LGD Data Automation, Methodology & Delivery Product Group is taking full ownership for sourcing, processing, manipulating and delivering high quality LGD Data while being the driving force to develop and expand automation efforts as well as integrating innovation such as AI technology into ING's CR data processes. 

Roles and responsibilities 

As a Data Analyst, we expect you to: 

• Play a key role in automating the sourcing and processing of credit risk data from multiple systems of record (SoRs).  

• Apply investigative approaches and enhanced logic to ensure high-quality output data that meets predefined thresholds for modelling purposes. 

• Manage the end-to-end process for sourcing, processing, and delivering datasets according to established frameworks and tools.  

• Take a proactive approach to continuously improve efficiency and accuracy in data operations. 

• Create and maintain clear technical documentation for development and operational workflows, ensuring compliance and supporting knowledge transfer within the team. 

• Contribute to the preparation of data and analytics reports, transforming complex datasets into actionable insights for stakeholders. 

• Advise and educate stakeholders on best practices for streamlining and standardizing data recording processes to ensure quality and consistency across systems. 

• Play a key role in automating the sourcing and processing of credit risk data from multiple systems of record (SoRs), ensuring compliance with predefined sanity thresholds for modelling purposes. 

Your competencies 

You are curious, proactive, and analytical, with a strong sense of ownership and drive for delivery. You thrive in complex environments and are comfortable navigating ambiguity, high-pressure situations and working towards challenging deadlines. 

Required skills and experiences 

• University / Postgraduate (Master’s degree) 

• General Experience: Experienced practitioner able to work unsupervised (13 months to 3 years) 

• Managerial Experience: Basic experience of coordinating the work of others (4 to 6 months) 

• Action oriented, Business Insights, Cultivates Innovation, Collaborates, Manages Complexity, Tech Savvy 

• Experience with SAS and Python, SQL is a plus 

• Dynamic programming 

• Good understanding of Credit Risk modelling concepts 

• Good understanding of Financial Risk management is a plus 

• A personality and the capabilities to function effectively and independently even in complex, high pressure situations 

• Strong analytical skills with the ability to translate complex data and information into actionable roadmaps and decision proposals 

• Excellent level of English