AdressWe are looking for a Student Assistant Quantitative analyst to our dynamic team in Collective Impairment Models that wants to work alongside writing their master thesis. The job provides an exciting mix of challenges for someone close to completing an academic degree, where different areas of knowledge and skills shall be employed: working with big data, creating expected credit loss framework, develop credit risk models, analyzing economic behavior, understanding and abiding to regulatory constraints and further, to explain complex models to stakeholders on all levels across the Bank. You will join a highly professional and dedicated team with a large network across the bank and with excellent opportunities for personal and professional development. This is a fixed time position until 21 June 2024 and offers limited working hours to leave time for writing a master thesis.
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 Collective Impairment Models team in Risk Models in Group Risk. Working with us, you will be part of one of the most important programs for the bank, which consists of upscaling Nordea's models and frameworks for internal expected loss. You will cooperate closely with your colleagues across the bank and you will have great possibilities to develop your skills within credit risk area - a field which is in high focus in Nordea.
What you will be doing:
- Develop quantitative models within the IFRS9 suite of credit risk models
- Defining solutions and frameworks for expected credit loss, ensuring internal model consistency for model use.
- Developing an impact tool in Python to simulate portfolio impact for various scenario analysis, including stress testing and macro sensitivities.
- Building strong relationship with different stakeholders within and outside the bank to facilitate understanding on our models and framework.
- Providing sharp data analytics to contribute to key decisions
You will join an open and inspiring atmosphere in a team, where we value being good colleagues. Your work life balance is important to us. We offer flexible working hours, remote work, generous leaves (including parental), time off and time to take care of sick children.
The role is based in Stockholm, Sweden.
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:
- Show quantitative analytical capability, proactivity and problem-solving skills. You are comfortable working with large datasets and enjoy finding solutions to loosely defined problems.
- Are a team player and can work closely with more senior analyst and contribute to a greater whole.
- Are dependable, willing to speak up even when it's difficult.
Your experience and background:
- You have recently completed an academic degree (MSc) except for the master thesis within a quantitative field, including but not limited to statistics, mathematics, or engineering
- Are writing a master thesis during H1 2024 and want to work limited hours in parallel
- Have a strong interest in working with programming languages and environments such as Python, SQL, Pyspark, Jupyterhub etc.
If this sounds like you, get in touch!
Next steps
Submit your application no later than 24/01/2024 . Interviews will be conducted on a rolling basis. For more information, you're welcome to contact Head of ECL Models Andreas Wirenhammar at andreas.wirenhammar @nordea.com.
For union information, please contact finansforbundet@nordea.se or SACONordea@nordea.com.
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.
Department: Credit and Risk management
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