Treasury Quantitative Strategist – Financing & Liquidity

Goldman Lloyds International; New York (NY); On-site; USD 220,000 - 360,000; Full time

Job summary

Goldman Lloyds International is seeking a Quantitative Strategist in New York to strengthen front-office quantitative capabilities across Treasury, financing, margin, and liquidity. The role sits at the intersection of Treasury, Quant Research, and Engineering to deploy capital efficiently across a multi-asset platform.

You will develop models for margin optimization, collateral allocation, and liquidity forecasting while collaborating with Treasury and investment teams to implement scalable

Qualifications

• Degree in a highly quantitative discipline (Math, Stats, Physics, CS, Engineering).
• Strong Python and/or C++ programming skills.
• Experience with large financial datasets and production-grade analytics.
• Understanding of Treasury, financing, margin, and liquidity concepts.

Responsibilities

• Develop quantitative models for margin, financing, collateral, and liquidity optimization.
• Analyse financing costs and capital usage across portfolios and asset classes.
• Build models around prime brokerage margin, haircuts, funding and collateral allocation.
• Research opportunities to improve balance-sheet and capital efficiency.
• Model liquidity requirements under various portfolio and market scenarios.
• Create scalable production tools for analytics and forecasting.
• Collaborate with Treasury, Quant Research and Engineering to implement solutions.

Skills

Python

C++

Quantitative modelling

Large datasets

Hedge fund experience

Education

Bachelor’s or higher in Mathematics/Statistics/Physics/CS/Engineering

Tools

SQL

NumPy/Pandas

Job description

Compensation: Competitive Base + Bonus

A leading multi-strategy investment firm is seeking a Quantitative Strategist to build and enhance quantitative capabilities across Treasury, financing, margin and liquidity. This is a front-office quantitative role sitting between Treasury, Quant Research and Engineering, focused on applying quantitative methods to the efficient deployment of capital across a complex multi-asset investment platform.

The Role

• Develop quantitative models for margin, financing, collateral and liquidity optimization
• Analyse financing costs and capital usage across portfolios and asset classes
• Build models around prime brokerage margin, haircuts, funding and collateral allocation
• Research opportunities to improve balance-sheet and capital efficiency
• Model liquidity requirements and funding under different portfolio and market scenarios
• Develop analytics for cash, financing and margin forecasting
• Work with Treasury and investment teams to understand the impact of portfolio changes on financing and liquidity
• Build research and analytics into scalable production tools
• Partner closely with Quant Developers and Treasury Engineers
• Take ownership from quantitative research and model design through implementation

Candidate Profile

• Experience within Treasury, Portfolio Finance, Prime Brokerage, Financing, Margin or Liquidity
• Strong quantitative background across optimization, statistical modelling and/or numerical methods
• Understanding of institutional financing, collateral and margin mechanics
• Strong Python and/or C++ experience
• Experience working with large financial datasets and building production-quality analytics
• Background within a hedge fund, investment bank, market maker or other sophisticated trading environment
• Degree in Mathematics, Statistics, Physics, Computer Science, Engineering, Financial Engineering or another highly quantitative discipline
• Particularly relevant for candidates who have worked on the sell-side financing/margin problem and want to own it from the buy-side