A global professional services company with a world-class reputation in investment banking and financial markets. This company is a leading provider of integrated risk management and regulatory services to banking and capital markets, insurance, asset management and government.
The quant team is responsible for building and maintaining modelling solutions, and providing analysis and consultancy to various clients across the banking and capital markets sector.
The senior quant will manage the quant team. The quant team employs a number of complex statistical techniques to build and deploy financial and risk models covering the retail secured lending sector. The team's core focus is delivering greater commercial impact and customer value by analysing, exploring and modelling data.
The Senior Quant will have a broad range of responsibilities including driving the ongoing improvement of existing products, and leading the quant team to deliver the long term product roadmap. In addition the Senior Quant will work closely with sales and business development to win and retain long term customers.
- Manage and grow a team of analysts to develop risk models for customers and represent the quant team to the wider business.
- Work with prospective customers to win new business, and existing customers to ensure the effective delivery of analytical and wider consulting solutions
- Conducting detailed analysis and quantitative modelling on secured retail product data, developing meaningful conclusions that adding value to the customers' lending strategy.
- End-to-end model development from concept to prototype, communication of key model features to internal stakeholders, liaising with data science and commercial teams at all stages of the model development
Description of the Candidate:
- 7 or more years` experience in applying complex analytics to business solutions, with a track record of resolving business challenges by applying traditional and inventive technical solutions
- A strong qualification, ideally at PhD level, in Finance, Economics, Mathematics, Physics, Engineering or a related quantitative field
- Expert working knowledge of one or more statistical packages including SQL (essential), R, SAS, Matlab (desirable)
- Experience of working in a data-rich environment with data mining techniques and predictive analytics, e.g. sampling, linear regression, logistic regression, time-series analysis, clustering, neural networks, genetic algorithms
- Previous experience of working within financial services or capital markets is essential, understanding of mortgages, credit cards or loans is desirable but not prerequisite
- Excellent communication skills both written and oral
- Strenuous attention to detail and strong emphasis on methodological integrity
- Previous experience of modelling secured retail products risk would be considered very advantageous