Senior Quantitative Researcher

The Role

We are seeking an exceptional Quantitative Researcher to join a high-growth systematic trading pod. This individual will be responsible for the full lifecycle of alpha discovery—from raw data ingestion and hypothesis testing to the design and implementation of automated trading strategies.

Key Responsibilities

1. Alpha Discovery: Extract signals from massive, noisy datasets (including structured market data and unstructured alternative data) using advanced statistical and machine learning techniques.

2. Strategy Design: Develop, back test, and optimize systematic trading strategies across multiple asset classes (Equities, FX, or Fixed Income).

3. Portfolio Construction: Collaborate with Portfolio Managers to refine risk-sizing, execution logic, and transaction cost modelling.

4. Data Innovation: Partner with Data Engineers to evaluate and integrate new alternative data sources (e.g., satellite imagery, credit card telemetry, or LLM-derived sentiment).

Required Qualifications

• Education: PhD or master’s from a top-tier institution in a quantitative field (Mathematics, Physics, Computer Science, or Financial Engineering).

• Technical Proficiency: Expert-level Python (NumPy, Pandas, Scikit-learn). Experience with C++ or Rust for production-level code is highly desirable.

• Statistical Depth: Mastery of time-series analysis, stochastic calculus, and machine learning (specifically reinforcement learning or deep learning applied to finance).

• Experience: 3–7 years of experience in a Quantitative Research role within a systematic hedge fund, proprietary trading firm, or the quant-strat desk of a major investment bank.

Candidate Attributes

• Competitive Drive: A "win-rate" mentality with a focus on delivering PnL.

• Scientific Rigor: The ability to maintain objective skepticism when analysing back test results.

• Communication: Able to distill complex mathematical concepts into actionable trading insights for non-technical stakeholders.