AI Risk Lead

1 month ago

Taastrup, Denmark Nordea Bank Full time

Job ID: 27376 

Are you ready to help shape the future of AI & Generative AI at Scandinavia's largest bank, working alongside a dynamic, fast-paced team?

The Group AI Center of Excellence is an established unit within Group Data Management focusing on delivering and enabling generative AI use cases across the organisation in a secure and compliant way. The unit provides reusable AI Assets that are developed in conjunction with business stakeholders to be leveraged by a wide variety of use cases.

We are now looking for an AI Risk Lead who is interested in Risk and Responsible AI topics, to apply in the field of Generative AI with use-cases across the bank. You will work closely with data scientists, ML engineers, and business stakeholders to ensure all AI and GenAI applications and use cases are development and deployed in compliance with the AI EU Act.

About this opportunity

Welcome to the Applied Data Science team. Your passion for working with people from both a technical and a business background, coupled with your curiosity for AI and new innovations like Generative AI, makes you well-suited for this position. As Nordea pioneers its way into an AI and Gen AI driven future, you will thrive by embracing a dynamic environment, fostering collaboration, and maintaining an open and adaptable mindset.

What you will be doing:

Support the design and ensure EU AI Act implementation plan across the organization Disseminate best practices, serving as a point of contact to all AI efforts, guaranteeing best practices on responsible AI are interestingly adopted in the Bank Educate use case owners and other relevant stakeholders in bank-wide risk protocols and external regulations Conduct research and ensure commitment in ethical standards of AI governance, such as fairness, accountability, transparency, privacy, and human rights

Our AI team culture is built on collaboration, continuous learning and innovation. We foster an open environment where diverse ideas thrive, encouraging everyone to push the boundaries of technology while supporting each other´s growth. With a strong focus on well-being, we prioritize work-life balance and encourage open communication.

At Nordea, inclusion and diversity are at the heart of our values. We believe that a diverse workforce drives innovation, fosters creativity and creates a more supportive workplace for all. The role is based in Høje Taastrup, Helsinki, or Stockholm.

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:

Embrace a growth mindset, where you enjoy taking initiative and bringing solutions Enjoy problem solving, and tackling challenges Are an awesome team member and you have a strong ability to inspire people to take action

Your experience and background:

BSc, MSc or PhD in Computer Science, Data Science, Risk Management, or a related discipline 10+ years of experience in AI Risk, Model Risk Management and related activities, with strong proven experience and familiarity with EU AI Act and other relevant AI regulations (GDPR) Strong communication skills, with the ability to prepare and drive presentations in multiple stakeholders meetings incl. clear alignment with C-level executives, as well as the ability to lead organization wide communication and deliver trainings to educate multiple stakeholders on responsible AI Extensive knowledge of GenAI and AI development and deployment process e.g., data exploration, feature engineering, production testing, and output validation Proven experience in managing AI-related risks projects, including identifying potential risks and designing mitigation strategies Professional experience in developing and implementing Data Management and Governance frameworks, including data quality, security, privacy and compliance processes and procedures Knowledge of AI & GenAI model mitigation processes for associated risks e.g. hallucination, fairness, explainability Knowledge of in AI/ML product development and working with MLOps best practices

If this sounds like you, get in touch

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