Quant Investment Associate, Portfolio Management

As a Quant Investment Associate, you will be the analytical engine behind our Fixed Income platform. You will not only build the models but also interpret the data to provide strategic recommendations on portfolio construction, tactical asset allocation, and risk-adjusted optimization. This is a highly visible, front-office role where your work directly impacts the alpha generation of our Fixed Income mandates.

Key Responsibilities

Portfolio Construction & Optimization

• Quantitative Modeling: Design and implement robust frameworks for multi-sector Fixed Income portfolio construction (including Sovereigns, Corporates, High Yield, and Securitized products).
• Optimization: Develop and refine optimization algorithms (e.g., Mean-Variance, Risk-Parity, or Factor-based) that account for transaction costs, liquidity constraints, and regulatory requirements (e.g., Basel IV/Solvency II).
• Asset Allocation: Support the PM in determining tactical shifts across duration, curve, and credit quality by modeling expected returns and risk premiums.

Investment Recommendations & Strategy

• Alpha Generation: Utilize systematic signals and alternative data to identify relative value opportunities across global fixed-income markets.
• Scenario Analysis: Conduct "Stress-Testing" and "What-If" simulations to quantify portfolio sensitivity to interest rate shocks, spread widening, or geopolitical events.
• Direct PM Collaboration: Present quantitative findings in a clear, narrative format to the PM, translating complex math into "Buy/Sell" or "Overweight/Underweight" recommendations.

Analytics, Tooling & Dashboards

• Custom Tooling: Build and maintain proprietary Python-based libraries for bond pricing, yield curve fitting, and attribution.
• Visual Dashboards: Develop real-time dashboards (using Streamlit, Dash, or Tableau) to visualize portfolio exposures, risk concentrations, and performance drivers.
• Ad-hoc Analytics: Rapidly respond to market events by performing deep-dive data analysis on specific sectors or idiosyncratic risks.

Qualifications

• Education: Masters or PhD in a STEM field (Financial Engineering, Mathematics, Physics, Statistics, or Computer Science).
• Experience: 3–10 years in a quantitative role within Fixed Income, ideally on the buy-side (Asset Management or Hedge Fund).
• Programming: Expert-level Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow). Experience with SQL and version control (Git) is essential.
• Fixed Income Mastery: Deep understanding of duration/convexity, credit spreads, OAS, and the mechanics of structured products or derivatives (CDX, Swaps, Futures).
• Communication: Ability to bridge the gap between "Quant" and "PM"—explaining technical methodologies to non-technical stakeholders.
• Commercial Acumen: A passion for markets and a drive to find profitable patterns in data.
• Agility: Comfortable in a fast-paced trading floor environment where priorities can shift based on market volatility.