Master’s degree required; advanced quantitative degree, computer science, mathematics/statistics, engineering, or financial engineering
2+ years of experience of experience risk management and/or risk quantitative analysis/modelling, and/or experience in a consultancy (with risk focus) and/or comparable experience in banking, risk regulation & compliance, capital markets, market risk, treasury & balance sheet management, trust & safety, insurance, non-financial risk, and ESG
Experience with AI agents or Agentic technologies
Familiarity with machine learning/AI (e.g., NLP, deep learning, anomaly detection) and GenAI/LLM is a plus
Exceptional conceptual problem-solving skills, along with deep analytical expertise and quantitative modeling experience, are highly valued
Ability to work collaboratively in a team and create an inclusive environment with people at all levels of an organization and capability to drive an independent workstream in the context of a broader team project
Experience with risk model lifecycle activities (development, implementation, testing) and programming in Python, R, or similar; knowledge of SQL, NoSQL, Matlab, or SAS is a strong advantage
Ability to communicate complex ideas effectively – both verbally and in writing – in English and the local office language(s)
Willingness to travel
