About the job Director - Credit Risk Analytics



Our client is looking to recruit a Director in their Dublin office, with hybrid working. This is a challenging and fulfilling role, with responsibility for delivering validation solutions in the areas of risk modelling in areas such as quantitative risk advisory, advanced analytics, risk measurement and strategy. There is a particular focus on second-line credit risk in banking, covering areas such as IRB, IFRS9, Stress Testing, Pillar 2 and Portfolio Management.




Role Responsibilities

• Leading assignments and engagements with banking clients in the areas of specialist quantitative and risk expertise


• Implementing bespoke quantitative and qualitative frameworks for the implementation of best in class end-to-end independent model validation


• Providing expertise and specialist knowledge input


• Lead the development of the firm and delivering on client facing engagements and assignments


• Ensuring the appropriate outcome of work is communicated clearly and effectively within internal reporting lines and to external stakeholders


• Providing on-going training and support to the team and on-boarding of new hires, particularly from a technical perspective

• Masters degree or equivalent professional qualification in either quantitative risk (modelling) business, accounting, finance, economics, maths, risk or any related professional discipline


• Ten plus years experience in relevant financial services roles


• Extensive experience of the banking sector, the practical operation of companies within that industry and quantitative risk management techniques and approaches


• Strong analytical, problem solving, decision making, planning and organisational skills


• Proven ability to critically assess complex issues and problems and identify solutions for root causes of issues


• Knowledge of the banking regulatory and legal framework and a deep understanding of the following: retail or wholesale business models, key risk drivers and supervisory approaches


• Excellent verbal and written communication


• Excellent capability in managing and delivering under tight timeframes


• Strong ability to utilise statistical/ coding packages such as (SAS, R, Python,VBA, C++)


• Excellent MS Word, Excel and PowerPoint skills