Quantitative Investment Strategist, Liquid Alternatives

Goldman Sachs; New York (NY); Presencial; USD 100 000 - 180 000; Tempo integral

Resumo da oferta

Goldman Sachs Asset Management seeks an Associate within the QIS Liquid Alternatives team in New York. You will contribute to researching hedge fund and private asset return drivers and help build systematic trading strategies that scale across assets.

You will work with senior portfolio managers and researchers, applying advanced econometric methods while handling large data sets to support strategy development and performance monitoring.

Qualificações

• Bachelor's, Master's or PhD in Financial Engineering, Statistics, Mathematics, Physics, Computer Science or a related quantitative discipline.
• 0–3 years of relevant experience (including internships).
• Strong foundation in statistics, linear algebra and calculus.
• Strong programming skills (Python, Matlab, R, C++ or other languages).
• Excellent analytical and quantitative skills, with keen attention to detail.

Responsabilidades

• Conduct quantitative research on hedge fund and private asset return data to identify replicable return drivers.
• Help develop cross-asset systematic trading strategies that fit within the broader factor tracking portfolio.
• Work with large structured and unstructured datasets to extract insights that inform systematic investment strategies.
• Contribute to the development, enhancement and maintenance of the research and portfolio management platform, spanning strategy backtesting, performance monitoring and risk analysis.

Conhecimentos

Programming skills

Analytical skills

Quantitative background

Team collaboration

Formação académica

Bachelor's/Master's/PhD in a quantitative field

Ferramentas

Python

Matlab

R

C++

Descrição da oferta de emprego

Goldman Sachs Asset Management seeks an Associate within the QIS Liquid Alternatives team in New York. You will contribute to researching hedge fund and private asset return drivers and help build systematic trading strategies that scale across assets.

You will work with senior portfolio managers and researchers, applying advanced econometric methods while handling large data sets to support strategy development and performance monitoring.