Treasury Senior Quantitative Researcher

Balyasny Asset Management L.P.
London
1 month ago
Applications closed

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Quantitative Developer (Low Latency) EMEA (F/M/D)

The Treasury Quant team at Balyasny Asset Management is expanding, and we are looking for a Senior Quantitative Researcher. The Treasury Quant team is responsible for firm-wide portfolio construction, globally, across all asset classes, aimed at minimizing margin, and contributing to maximizing the Firm’s liquidity buffer.


The Quantitative Researcher will:

· Develop and implement internally consistent risk-based models for margin allocation and optimization, across all asset classes

· Constantly review and upgrade margin allocation models.

· Design and implement margin optimization processes for different asset classes

· Enhance the analytics suite used by the treasury team to measure and manage capital utilization and allocation

· Analyze and approximate various house and reg margin methodologies, including cross-margin

· Collaborate with the risk team to leverage their offering for margin methodologies

· Create risk-based explain tools for margin allocation and drivers

· Work with Portfolio Managers and Business Leaders to refine margin attribution models

· Help expand product coverage and methodologies used for various margin calculators and treasury specific analytics tools for efficient capital deployment

· Expand the quantitative framework for managing the firm’s liquidity, cash and collateral deployment

· Design, prototype, test, and implement risk-based margin models


Qualifications and Requirements

· 10 or more years of experience in Quantitative Research at Hedge Funds, Banks, and/or Asset Managers within a Front Office, Treasury and/or Risk team

· STEM PhD or MS degree

· Hands on experience solving optimization problems and in depth experience with at least 1 optimization engine – Mosek preferred. Real world optimization implementation expertise required

· In depth modeling experience

· Excellent hands-on programming skills in Python (including numpy, scipy, Pandas)

· Expected to deliver asset specific allocation and optimization libraries in Python

· In depth knowledge and experience in Equities, Fixed Income, Credit and/or Commodities

· Direct involvement in building a margin methodology

· Ability to work on several projects simultaneously

· Innovative, flexible, open approach to solving real-life problems

· Experience with being responsible for projects spanning several teams (PMs, risk, IT, etc)

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