Quantitative specialist for developing and managing analytics for counterparty credit risk models. Candidate will join the Risk Analytics group that partakes in model development over the full life-cycle of modes: from methodology to design to local implementation and validation. The successful candidate will also provide analysis and feedback on changes to or introduction of new models at the firm.
Responsibilities
- Develop and implement analytics for counterparty credit risk management.
- Build infrastructure to consolidate counterparty credit risk models across systems.
- Create and execute strategies to minimize risk based capital required by regulation.
- Perform quantitative research to implement model changes, enhancements and remediations.
- Work with stakeholders across business and functional teams during model development process.
- Create tools and dashboards which can enhance and improve the risk analysis.
- Conduct analysis on existing model short-comings and design remediation plans.
- Maintain, update and back-test risk models.
- Develop Risk Analytics platform.
- Assess the methodologies and processes used by modeling teams to develop and manage their models, and identify potential weaknesses and the associated materiality of the risk
Qualifications
- At least a Master’s Degree in quantitative subject; PhD Degree is a plus.
- Deep understanding of pricing and risk calculations for financial derivatives.
- Strong analytical skills required to understand quantitative models, and to translate that understanding into sustainable library design, code development and integration into IT systems.
- At least 3-5 years of experience in counterparty credit risk modeling.
- Strong project management and organizational skills.
- Proficient programming skills in python (other languages such as R is a plus).
- Strong programing skills and data handling skills in SQL and R/Python (ability to wrangle large data sets, implement statistical tests, and perform data analysis on test results).
- Excellent written skills (ability to produce well-structured technical model documentation).
- Knowledge of Numerix and/or Bloomberg a plus.
