Beschreibung

Your contribution to KPMG ##

• Develop, validate and enhance quantitative models for financial risk management, including market, credit, liquidity and other banking risk topics.
• Analyse large and complex datasets, perform statistical testing and translate results into clear and actionable insights for clients.
• Build robust and well-documented analytical solutions using Python and relevant quantitative libraries.
• Apply machine learning, generative AI and automation techniques to improve modelling, validation, reporting and risk management processes.
• Support client engagements from analysis and solution design through implementation, testing and documentation.
• Prepare high-quality presentations and communicate technical findings clearly to both specialist and non-specialist stakeholders.
• Contribute to internal quantitative and AI capabilities, reusable tools, proofs of concept and market initiatives.
• Stay informed about regulatory developments, modelling practices and emerging AI technologies relevant to financial institutions.

This is what makes you successful ##

• Master's degree in quantitative discipline such as mathematics, statistics, physics, quantitative finance, data science, computer science or engineering.
• 0-2 years of relevant experience in quantitative modelling, model validation, risk analytics, data science or related consulting; strong graduates may also be considered.
• Good understanding of machine learning and AI concepts; hands-on experience with Generative AI, large language models or AI-enabled automation is an advantage.
• Interest in financial services and risk management; knowledge of market, credit, liquidity or model risk is an advantage.
• Structured problem-solving skills, attention to detail and the ability to explain quantitative topics clearly.
• Fluent English and German, and French is beneficial.