We are working with one of the world's leading quantitative trading and investment firms, seeking a Multi-Asset Portfolio Researcher to join their firm. Please see role details and qualifications below:

Principal Responsibilities

• Development of multi-asset class analytics across all MLP strategies, supporting the Office of the CIO across Enterprise-wide initiatives
• Building a multi-asset class risk and pricing analytics framework. This includes performance attribution, working with relevant asset class pricing model libraries.
• Contributions to the development of multi-asset class content generation as well as centralized visualization tools for the platform used by senior management
• Ownership in developing a quantitative framework for identifying, measuring, managing, and reporting multi-asset class analytics across the platform
• PM performance measurement and analytics to help inform management decisions
• Ownership of a multi-asset class stress-testing framework, including research on multi-asset class hedging strategies
• Capital utilization and allocation models across PM teams. Cost of liquidation measurement and management, as well as associated returns relative to constrained resources
• Post initial model development work, coordinate with relevant Technology departments to ensure changes are deployed into to production

Qualifications/Skills Required

• Multi-asset or Fixed Income (e.g. rates, credit, mortgages) experience, with hands on experience with developing and maintaining risk and/or derivative pricing models
• The candidate should have a graduate degree in a quantitative major: statistics, mathematics, engineering, and either professional experience of 10 years in a quantitative role in a financial organization, or a MS in financial engineering/economics.
• Strong programming skills, prior experience with Python (Polars and/or Pandas). Proficiency in at least a compiled and statically typed language is a plus
• Knowledge of mathematical and statistical analytics tools: estimation of linear models, dimensionality reduction techniques e.g. Equity Factor Models, Principal Component Analysis, etc.
• Sense of responsibility and integrity. Intellectual curiosity and spirit of initiative. Willingness to work and have fun in the process.
• Good presentation and communication skills, experience in either preparing or participating presentation for senior management-style meetings.