Counterparty Credit Risk Quantitative Analyst at LevelUP HCS in New York, New York

Posted in Other 3 days ago.

Type: full-time





Job Description:

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.

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