Quantitative Analyst I Brokerage Firm

We are seeking a talented Quantitative Analyst to join our team. You will design, develop, and validate the models, analytics, and tooling that underpin our pursuit of best execution across asset classes. Working at the intersection of market microstructure, statistics, and software engineering, you will measure execution quality, optimise routing and algorithm selection, and provide the evidence base that demonstrates the firm is delivering the best possible outcome for every order.

What will you do:

• 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.

Who are we looking for:

• 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 stats models.
• 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.