Masters degree or PhD in Mathematics, Physics (non-experimental), Probability/Statistics, Engineering, or (Mathematical) Finance
Familiarity with asset-backed structured products, Intex and data analysis or empirical modelling is a strong plus
Minimum of 3 years of relevant professional experience at a top sell-side or buy-side institution in a front office quantitative role
Exceptional quant / analytical skills – knowledge of advanced pricing techniques, asset pricing theory (including risk neutral, CAPM), probability theory, and cash flow / bond maths (e.g. OAS calculations)
Experience designing, coding, and implementing pricing and surveillance frameworks for automation / streamlining of tasks
Strong coding skills in Python – candidates for whom Python experience is limited to occasional / hobby usage should not apply
Experience with structuring / liability-side (e.g. SPV mechanics) aspects of finance a big plus
Working knowledge of Linux/Unix/Bash and SQL would be a plus
Responsibilities
Perform initial value deal assessments via data analysis, modelling and pricing of fundamental risks, and relative value (across capital structures and asset classes) analyses
Provide post-trade support by monitoring and reporting on collateral and trade performance (surveillance)
Support Portfolio Managers in their investment and asset management decisions
Develop new pricing models and implement them into Python code
Develop new approaches to pricing bespoke transaction features
Work with, and contribute to, large coding infrastructures
Work closely with Portfolio Managers and build strong relationships