QUANTITATIVE INVESTMENT ANALYST

QUANTITATIVE INVESTMENT ANALYST

Posted - 18 Oct 2023

Location - MONACO / LONDON

Our client is an established Single Family Office looking to add a Quant Analyst to their small, Monaco based team.

They invest in multiple asset classes which include Hedge Funds, Private Equity, Private Debt, Equities, Bonds, Currency Overlays and various Derivatives. Analysis and Due Diligence are all conducted in house and this role will entail the review and analysis of both incoming opportunities and the existing portfolio.

The successful candidate will have a strong academic background in a quantitative subject such as Mathematics, Physics, or Computer Science.

This opportunity will suit someone who thrives when working autonomously in a small team, with high caliber colleagues.

The successful candidate will likely have experience of public equity trading and derivatives and have in depth understanding of balance sheets, and how a company works.

Whilst financial market experience (such as working for a Fund of Funds, Investment Bank or Family Office) is advantageous, the critical need is for very strong quantitative analysis skills and expertise.

Programming skills: there is a strong preference for proficiency with SQL & DAX, as well as familiarity with Power BI, Monte Carlo techniques, Data mining and Dynamic Modeling.

The candidate will need to be able to create, implement, and support quantitative models for portfolio construction, portfolio management and risk management of both potential and existing investments as well as develop allocation models using numerical techniques for valuation including Monte Carlo Methods.

The role is ideally based in Monaco although there may be some flexibility, but frequent and regular visits will be a prerequisite.

For further information or if you would like to apply for this role, please send your CV to Shabana Saeed at shabanas@agreusgroup.com

Remuneration will be commensurate with the duties and demands of the role and the experience of the candidate.

REF: AGR793