2 дня назад
Assistant Vice President, Quant, Structured Finance Analytics
69 000 - 104 467€
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Assistant Vice President, Quant, Structured Finance Analytics (Python/C++): Building quantitative credit rating models and analytics solutions for ABS, CMBS, RMBS, and structured credit with an accent on predictive modelling, structured datasets, and proprietary research. Focus on developing scalable ingestion, storage, training, inference, and validation systems while applying numerical methods to default and loss modelling.
Location: Frankfurt, Germany; hybrid work with four days in the office each week
Base salary: EUR 69,000–104,466.66 annually, plus a 20% annual bonus target.
Company
provides credit ratings and analytical tools, with a global Structured Finance Analytics team located across the US and Europe.
What you will do
- Support rating methodology development and implement quantitative credit predictive models.
- Develop, maintain, and enhance proprietary Python and C++ libraries for model building.
- Use structured and unstructured datasets to create quantitative frameworks supporting analyst decision-making.
- Design and develop analytics solutions for scalable information ingestion, storage, computation, training, inference, and validation.
- Collaborate with Credit Ratings, Credit Practices, Methodology Review, Data Engineering, and Technology teams.
- Contribute to quantitative research papers supporting model development and methodology enhancements.
Requirements
- Bachelor’s degree in mathematics, engineering, physics, economics, finance, statistics, or a related quantitative discipline; a Master’s degree or PhD is preferred.
- At least five years of experience within a rating agency.
- At least five years of hands-on experience modelling RMBS, ABS, and CLO defaults and losses.
- Programming experience in Python or C++, plus experience writing research articles or technical documentation with LaTeX.
- Strong knowledge of statistical modelling, probability theory, numerical analysis, stochastic calculus, numerical integration, Monte Carlo simulation, root-finding, and optimisation.
- Excellent understanding of securitisation products and the ability to bridge business and technical requirements.
Nice to have
- CQF or a postgraduate degree in quantitative finance, economics, or a STEM field.
- Experience with NumPy, Pandas, Scikit-Learn, and SciPy.
- Experience performing rigorous analysis on large datasets.
- Experience developing cloud applications, preferably on AWS.
Culture & Benefits
- Hybrid collaboration with regular in-person work and tools for engaging with global colleagues.
- Additional benefits are available to support changing flexibility needs.
- Personal and related investments must be disclosed confidentially to the Compliance team and may be subject to Code of Ethics review.
- Certain employee accounts may be required to be held with an approved broker depending on department and work location.
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