Position Overview

We are looking for a Quantitative FX Research Analyst to investigate currency-market behaviour, develop statistical models, and evaluate data-driven approaches to foreign exchange analysis. This position focuses on quantitative research, historical market-data analysis, volatility modelling, and the identification of statistically meaningful patterns across currency pairs.

The successful candidate will work with market data, economic indicators, and analytical tools to improve understanding of currency-price behaviour and support research-driven trading and risk decisions. The role requires a combination of financial-market knowledge, statistical competence, programming ability, and sound research judgement.

This opportunity is suitable for an analytical professional who enjoys solving complex problems, testing hypotheses, and translating quantitative findings into practical insights for financial-market teams.

Key Responsibilities

• Collect, clean, validate, and analyse historical and intraday FX market data across relevant currency pairs.

• Develop and evaluate statistical models for exchange-rate behaviour, volatility, correlation, and market-regime changes.

• Research relationships between macroeconomic variables, interest-rate expectations, liquidity conditions, and currency-price movements.

• Design backtesting frameworks to assess quantitative hypotheses and trading signals using historical data.

• Evaluate model performance using appropriate statistical measures while accounting for transaction costs, slippage, data quality, and potential overfitting.

• Conduct time-series analysis, regression modelling, correlation analysis, and other quantitative investigations relevant to FX markets.

• Build analytical tools and reproducible research workflows using Python, R, SQL, or comparable technologies.

• Investigate changes in volatility, market liquidity, price behaviour, and relationships between currency pairs.

• Prepare technical research notes, model documentation, visualisations, and presentations for traders, risk specialists, and other stakeholders.

• Work with technology teams to improve market-data pipelines, research datasets, and the efficiency of quantitative analysis.

• Monitor model assumptions and analytical limitations, documenting circumstances in which findings may no longer be reliable.

• Apply appropriate data governance, research validation, and internal control standards to all analytical outputs.

Qualifications and Technical Skills

• A degree in Quantitative Finance, Financial Engineering, Mathematics, Statistics, Econometrics, Computer Science, or a related field.

• Experience in quantitative research, financial-data analysis, systematic trading research, or a comparable analytical role.

• Strong knowledge of probability, statistical inference, regression, time-series analysis, and financial-market data.

• Proficiency in Python for data analysis and modelling, including familiarity with libraries such as pandas, NumPy, SciPy, and statsmodels.

• Working knowledge of SQL and structured data management.

• Familiarity with FX market conventions, currency pricing, volatility, spreads, and liquidity dynamics.

• Experience designing backtests and evaluating model robustness using out-of-sample testing or walk-forward validation.

• Understanding of common research pitfalls, including look-ahead bias, survivorship bias, overfitting, and inappropriate data selection.

• Ability to explain quantitative results to both technical and non-technical audiences.

• Strong documentation habits, intellectual curiosity, and a commitment to reproducible research.

Preferred Experience

Experience with tick-level or intraday market data, volatility forecasting, regime detection, execution-cost analysis, or quantitative signal research would be advantageous. Familiarity with cloud-based analytical environments, version control, and automated research pipelines is also beneficial.

Ideal Candidate

The ideal candidate combines programming proficiency with a sound understanding of financial-market behaviour. They approach model development systematically, challenge results that appear too good to be true, and understand the difference between statistical significance and practical usefulness.

They should be capable of working independently on research questions while collaborating with trading, engineering, and risk teams to ensure that analytical findings are interpretable, reproducible, and relevant to real market conditions.

Performance Expectations

Success will be measured by the quality and reproducibility of research, reliability of data-processing workflows, robustness of model validation, and usefulness of analytical findings. Particular importance will be placed on sound statistical methodology, transparent assumptions, and the ability to identify the limitations of quantitative models.

What We Offer

• An opportunity to work on quantitative problems in international foreign exchange markets.

• Exposure to financial time-series analysis, statistical modelling, and systematic research.

• Collaboration with experienced professionals across trading, technology, and risk functions.

• Opportunities to develop advanced programming and quantitative-finance expertise.

• A professional environment that prioritises research integrity, technical quality, and continuous learning.

Application focus: Candidates should highlight relevant quantitative projects, programming experience, FX or financial-market research, and examples of statistical models or analytical workflows they have developed and validated.

Are you interested in this position?

Apply by clicking on the “Apply Now” Button below!

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