Role Overview

Our client, a leading global investment firm, is seeking a Front Office Desk Quant to partner closely with Portfolio Managers and Traders within the Macro and Relative Value (RV) investment team. The role focuses on quantitative research, pricing methodologies, risk analytics and systematic strategy development across Rates products, including swaps, swaptions, IRS and curve/RV trading strategies. You will work at the intersection of quantitative research and front-office investing, developing analytical frameworks and decision-support tools that underpin investment and trading decisions.

Key Responsibilities

1. Partner with Portfolio Managers and Traders to research, validate and support Macro and Relative Value investment strategies.
2. Develop and enhance pricing, risk and valuation methodologies for Rates products, including swaps, swaptions and interest rate derivatives.
3. Design and maintain quantitative models covering risk analytics, P&L attribution, Greeks and pre-trade analytics.
4. Research quantitative investment signals using statistical techniques such as PCA, factor models and time-series analysis.
5. Build and maintain robust back testing frameworks to validate systematic trading strategies and investment ideas.
6. Investigate pricing, market data and P&L discrepancies, working closely with quantitative and technology teams to enhance analytical methodologies.
7. Prototype analytical tools and research models using Python, Excel or similar technologies before collaborating with developers for production implementation.
8. Present quantitative research, analytical findings and methodology enhancements to Portfolio Managers and Traders to support investment decisions.

Required Skills & Experience

1. 4+ years of experience in a Front Office Desk Quant, Quantitative Research or Quantitative Analytics role supporting Portfolio Managers or Traders.
2. Strong understanding of Rates products, including swaps, swaptions, yield curves and interest rate derivatives.
3. Experience developing pricing models, risk methodologies and quantitative analytics within Front Office environments.
4. Strong Python programming skills for quantitative research, modelling and analytical tool development.
5. Solid understanding of quantitative methods, including statistical analysis, factor models, PCA and backtesting methodologies.
6. Experience with market risk analytics, including VaR, P&L attribution and portfolio risk analysis.
7. Excellent analytical and problem-solving skills, with the ability to communicate quantitative concepts to investment professionals.

Preferred Experience

1. Experience supporting Macro or Relative Value investment strategies.
2. Knowledge of curve trading, spread trading, carry/roll analysis or cross-market relative value strategies.
3. Experience designing and maintaining systematic research and backtesting frameworks.
4. Familiarity with financial market data platforms and market data APIs.
5. Experience working with Python scientific libraries and relational databases.
6. Exposure to quantitative research or investment analytics within hedge funds, asset managers or investment banks.