Credit Risk Business / Data Analysts, Group Credit Management
Stockholm, SE, 111 46
Nordea
Nordea is a leading Nordic universal bank – we are a strong and personal financial partner with financial solutions that best meet your needs so you can achieve your goals and realise your dreams.Job ID: 26367
Would you like to be part of a Nordic team, developing the future credit processes for our customers? We are now looking for Credit Risk Business / Data Analysts to our High Risk Data & Default Management Team.
We are offering you an exciting opportunity to develop key capabilities at the heart of Nordea. Your work will require you to understand the connection between regulatory requirements, business processes and data to pro-actively drive initiatives and solve complex problems connected to Nordea’s Credit Risk process.
About this opportunity
Welcome to the High Risk Capability team. We are a growing team, driving the development for high risk credit processes (such as default management and early warnings). Our aim is to build sustainable processes and supporting tools that cater for automation through which we enable great customer experiences. You will work closely with team members and relevant stakeholders to drive the implementation of new solutions and processes for business, regulatory and data requirements.
What you’ll be doing:
- Building expertise of Nordea’s credit risk agenda, especially within high risk
- Be part of an agile structure, with focus on defining, prioritizing and driving analysis and change initiatives from initiation to successful delivery, in close collaboration with development teams, relevant stakeholders and management
- Ensuring our solutions meet business and regulatory requirements and maximize business value
- Identifying and actively proposing improvements to streamline the end to end credit processes and enable automation in the area
You’ll join a diverse, multi-faceted and passionate team. Occasional travel primarily in the Nordics should be expected. The location is preferably in Sweden or Finland.
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.
Your experience and background:
- At least 2 years of experience working with data analysis and / or regulations and business processes within credit risk, preferably within high risk
- As a business analyst you have experience driving change (from gathering business / regulatory requirements to implementation) in an agile environment. You are also strong in documenting and conceptualising requirements in complex environments
- As a data analyst you naturally have a passion for data, working independently with data analysis to produce actionable outcomes with key insights for stakeholders
- Have a professional level of English, both written and spoken
- Have excellent communication skills, both verbal and written, building strong relationships with stakeholders across Business and IT
To succeed in the role, we believe that you:
- Can effectively deliver and prioritize tasks in a fast-paced environment
- Are self-going with a natural “can do” attitude, show ability to learn quickly and have a solution-oriented mindset supported by structured, analytical and creative thinking
If this sounds like you, get in touch!
Next steps
Submit your application no later than 19/12/2024 . For more information, you’re welcome to contact Matthew Woodward, matthew.woodward@nordea.com or +46 766960974.
At Nordea, we know that an inclusive workplace is a sustainable workplace. We deeply believe that our diverse backgrounds, experiences, characteristics and traits make us better at serving customers and communities. So please come as you are.
Please be aware that any applications or CVs coming through email or direct messages will not be accepted or considered.
For candidates in Sweden: For union information, please contact finansforbundet@nordea.se or SACONordea@nordea.com.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Credit risk Data analysis
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