We're currently partnered with a highly technical multi-asset prime brokerage and clearing firm that is building the systems that are going to connect all networks / exchanges / brokers into one unified platform. With a presence across the world, they are looking to add a strong quant to develop models for regulatory capital calculation and liquidity stress testing. The position is remote, but they are targeting a NY - based candidate for occasional in-office responsibilities.
Role:
- Develop and prototype models for regulatory capital calculation and liquidity stress testing, compliant with various jurisdictions.
- Implement scalable, supportable models for capital and liquidity management in collaboration with the Engineering team.
- Develop historical analysis and perform data research to back capital & liquidity models.
- Ensure balanced focus on internal management and external reporting for both capital and liquidity.
- Deploy production-grade code and manage data pipelines as a full-time member of the Engineering team.
- Work closely with Risk, Structuring, Finance, and Compliance teams for regulatory interpretations, focusing equally on capital and liquidity management.
Skills Needed:
- Experience in quantitative finance, particularly in asset classes affecting liquidity and capital.
- Data science, specifically Python and SQL for model development
- Proven ability in building and integrating processes into the firm's strategic architecture, with a focus on capital and liquidity.
- Proficient in large-scale, production-grade coding
Education and Experience:
- Degree in a technical or quantitative subject, with a strong preference for a graduate degree.
- Minimum 8 years of experience in quantitative finance and engineering roles.
- Proven experience in regulatory interpretation and reporting, especially in IFPR, EMIR regimes, and their application to prime brokerage, secured financing, and digital assets.
- Experience working alongside other engineers and in managing data pipelines
