Quantitative Analyst I Brokerage Firm

We are seeking a talented Quantitative Analyst to join our team. You will design develop andvalidate the models analytics and tooling that underpin our pursuit of best execution acrossasset classes. Working at the intersection of market microstructure statistics and softwareengineering you will measure execution quality optimise routing and algorithm selection andprovide the evidence base that demonstrates the firm is delivering the best possible outcome forevery order.

What will you do:

• Develop and maintain quantitative models for transaction cost analysis (TCA) marketimpact slippage and venue/algorithm performance.
• Conduct rigorous statistical analysis on tick order and execution data to identify sourcesof cost latency and information leakage.
• Build and maintain simulation and backtesting frameworks to evaluate executionalgorithms smart order routing logic and venue selection under varied market conditions.
• Partner with traders execution engineers and brokers to translate research intoimprovements in live trading and order routing systems.
• Produce regular best execution reporting for internal stakeholders and investigate outliersor deteriorations in execution quality.
• Research advances in execution science optimal trading market impact modelling andmachine 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 acrossall execution analytics work.

Who are we looking for:

• Masters 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 algorithmictrading.
• Strong proficiency in Python; familiarity with libraries such as NumPy pandas scikit-learnand 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 orderbook or execution data.
• Deep knowledge of market microstructure execution algorithms and smart order routingacross lit dark and auction venues.
• Exposure to cloud platforms (AWS GCP or Azure) and modern data infrastructure (SQLParquet kdb).

Skills & Attributes

• Analytical rigour: structured thinker who can decompose ambiguous problems into testablehypotheses.
• 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 constructivechallenge.