Senior/Quantitative Risk Analyst, Credit Risk Data Analytics
2 months ago
Job ID: 25760
Do you enjoy working with data analysis? Do you like solving problems and find out new and innovative solutions? Do you understand the principles of banking and are you able to apply this knowledge in your daily work?
We are looking for a Senior or Quantitative Risk Analyst to join Credit Risk Data Analytics team that is recognised for its professionalism, competence and capabilities. We have an ambitious development plan for the Risk models and together with our colleagues in Nordea we’ll be part of creating the future of banking.
At Nordea, we use internal models for calculating regulatory capital and these models are developed and maintained by Risk Models. This includes the data asset that collect and aggregate data from most of Nordea’s data landscape. Data analytics is in the core of statistical modelling to create an understanding of the data that’s used for modelling.
At Nordea, we’re committed to being a partner our customers and society can count on. Compliance and integrity go hand in hand. Joining us means you’ll have an impact on how we do banking – today and tomorrow. So bring your ideas, skills and unique background. With us, you’ll be in good company with plenty of opportunities to collaborate, grow and make your mark on something bigger.
About this opportunity
Welcome to the Credit Risk Data Analytics team, a part of Risk Models organisation.
We add value to Nordea and our customers by improving Nordea data quality, helping visualising and create the understanding of our data so modelling teams can build great models, finance can calculate profitability and the bank advisors can make credit assessments.
As a (Senior) Quantitative Risk Analyst, you play a valuable role in performing technical data analysis in UDM, which is a database built on Hadoop. Your role will also include coordinating data related activities and ensuring proper communication within the team and across other Risk model areas.
What you’ll be doing:
Different types of quantitative data analysis such as:- Data reconciliation
- Root-cause analysis for data quality issues
- Data extraction based on desired content
- Refinement of business requirements
Take responsibility for data related deliveries Communicate status to relevant stakeholders Performing data governance tasks as defined in Data Governance Recipe Preparing reports and other documentation used for both senior management and external reporting On occasions you will act as a bridge between business and IT, and ensure correct understanding between both partiesYou’ll join an international team with variety of backgrounds and skills. We believe that strong drive and passion for change are fundamental for delivering on our commitments. Bring your background and skills to our team, and you will have plenty of opportunities to collaborate, grow and develop.
The role can be based in Denmark, Finland, or Poland.
Who you are
Collaboration. Ownership. Passion. Courage. These are the values that guide us in being at our best – and that we imagine you share with us.
To succeed in this role, we believe that you:
Have an adaptability to thrive in fast-paced and dynamic environment Are structured and able to coordinate several deliveries simultaneously Are self-driven and able to work independently but also enjoy collaboration with others Have strong analytical skills and keen attention to detail with the ability to analyse complex data and processes to derive meaningful insights Have good communication and presentations skills, are not afraid to speak up and can effectively convey business requirements to IT teams and facilitate collaboration between stakeholders Are curious and proactive, focus on solutions rather than problems and share our enthusiasm for developing and learning and constantly improving your skills and competencesYour experience and background:
An interest in finance and technology Experience working with data analysis in a database structure Understanding of the credit risk area, particularly working previously with credit risk data would be an advantage but is not a prerequisite Knowledge of SQL, SAS, Python or similar Experience with Big Data would be an asset Master’s degree in finance, economics, engineering, physics, mathematics or a great reason for not having oneIf this sounds like you, get in touch
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