Senior Vice President, Quant, Structured Finance Analytics | Quantitative Analyst, Securitisation (Structured Finance)

Location: London, United Kingdom; hybrid work with in-office collaboration each week, typically four days in-office.

Base salary: GBP 134,700.00–195,566.66 annually, with a 30% annual bonus target.

Company

hirify.global provides credit ratings, analytical models and data-driven tools for assessing structured finance credit risk.

What you will do

• Own the design, implementation and enhancement of structured finance credit models across RMBS, CMBS, ABS and structured credit.
• Lead complex model and methodology development projects through release, coordinating technical workstreams, dependencies, timelines and stakeholders.
• Develop, maintain and enhance proprietary Python and C++ modelling libraries, including ETL processes for new datasets.
• Translate rating analysts’ analytical needs and market trends into transparent, interpretable modelling approaches.
• Prepare quantitative research papers and technical documentation; review models, mathematical derivations, code and validation results.
• Mentor quantitative analysts and explain complex quantitative concepts, assumptions, results and limitations to non-technical colleagues.

Requirements

• Master’s degree or higher in Mathematics, Engineering, Physics, Economics, Finance, Statistics or a related quantitative discipline; a PhD is preferred.
• At least 10 years of relevant professional experience in quantitative credit risk, including substantial hands-on development of structured finance default and loss models for RMBS, CMBS, ABS and/or CLOs.
• Practical experience with factor models, roll-rate models and survival models.
• Strong programming skills in Python or C++, experience with rigorous analysis of large datasets, and experience writing research articles or technical documentation.
• Deep knowledge of statistical modelling, probability theory, stochastic calculus and numerical methods, including numerical integration, Monte Carlo simulation, root-finding and optimisation.
• Strong mathematical and modelling judgement, with the ability to create simple, transparent and interpretable models without compromising analytical rigour.
• Excellent understanding of securitisation products and experience delivering complex quantitative projects with multiple teams and interdependent workstreams.
• Strong organisational, communication and teaching skills, including the ability to explain quantitative topics to non-technical audiences.
• Experience mentoring quantitative analysts and reviewing credit models and mathematical derivations.

Nice to have

• Experience working within or with a credit rating agency.
• For C++-focused candidates, familiarity with NumPy, Pandas, Scikit-Learn and SciPy.
• Experience developing cloud applications, preferably with AWS.
• Experience using LaTeX for research articles or technical documentation.

Culture & Benefits

• Hybrid work model focused on regular in-person collaboration, typically four office days per week in most locations.
• Tools and resources for meaningful collaboration with global colleagues.
• Additional benefits are available to support flexibility as needs change.
• Accepted candidates must confidentially disclose personal and related investments for Compliance review; applicable employee accounts may need to be held with an approved broker.