Trading Analyst (Forex)

Key Responsibilities

• Develop and maintain quantitative models for transaction cost analysis (TCA), market impact, slippage, and venue/algorithm performance.

• Conduct rigorous statistical analysis on tick, order, and execution data to identify sources of cost, latency, and information leakage.

• Build and maintain simulation and backtesting frameworks to evaluate execution algorithms, smart order routing logic, and venue selection under varied market conditions.

• Partner with traders, execution engineers, and brokers to translate research into improvements in live trading and order routing systems.

• Produce regular best execution reporting for internal stakeholders and investigate outliers or deteriorations in execution quality.

• Research advances in execution science — optimal trading, market impact modelling, and machine learning applied to microstructure — and assess their practical application.

• Document research findings clearly and present results to both technical and non-technical stakeholders.

• Maintain rigorous standards of model validation, code quality, and documentation across all execution analytics work.

Required Qualifications

• Master's or PhD in a quantitative discipline such as Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or Econometrics.

• 3+ years of relevant work experience in a quantitative role covering FX or commodities (or both), ideally with exposure to execution, TCA, market microstructure, or algorithmic trading.

• Strong proficiency in Python; familiarity with libraries such as NumPy, pandas, scikit-learn, and statsmodels.

• Solid grounding in probability theory, statistics, linear algebra, and stochastic calculus.

• Experience working with large datasets and writing clean, performant, well-tested code.

• Demonstrated ability to translate research into production systems.

• Excellent written and verbal communication skills.

Preferred Qualifications

• Hands-on experience applying machine learning techniques to high-frequency, order book, or execution data.

• Deep knowledge of market microstructure, execution algorithms, and smart order routing across lit, dark, and auction venues.

• Exposure to cloud platforms (AWS, GCP, or Azure) and modern data infrastructure (SQL, Parquet, kdb+).

Skills & Attributes

• Analytical rigour: structured thinker who can decompose ambiguous problems into testable hypotheses.

• Intellectual curiosity: eager to explore new methods and challenge prevailing assumptions.

• Attention to detail: careful with data quality, model assumptions, and numerical precision.

• Pragmatism: balances theoretical elegance against real-world constraints and deadlines.

• Collaborative: thrives in a small, cross-functional team and welcomes constructive challenge.