Company Overview

An international financial technology environment is expanding its quantitative trading capabilities to support data-driven investment strategies, systematic market analysis, and advanced electronic trading operations. Its trading infrastructure combines market data analytics, statistical modelling, automated execution technology, and risk monitoring systems across multiple financial markets.

The organisation is seeking a Quantitative Trading Researcher to develop and evaluate mathematical models, identify market patterns, and support the design of systematic trading strategies. The successful candidate will combine strong quantitative skills with practical knowledge of financial markets and the ability to translate research findings into measurable trading insights.

Role Summary

The Quantitative Trading Researcher will conduct research into financial market behaviour, develop statistical models, and evaluate quantitative strategies across supported asset classes. The role involves analysing historical and real-time market data, testing trading hypotheses, assessing strategy performance, and collaborating with software engineers and trading professionals to improve systematic trading capabilities.

The position requires a rigorous research approach, strong programming skills, and a clear understanding of statistical validity, market microstructure, and trading risk.

Key Responsibilities

• Conduct quantitative research across foreign exchange, equities, indices, commodities, and other supported financial instruments.

• Develop statistical and mathematical models to identify market patterns and potential trading opportunities.

• Analyse historical and real-time market data to investigate price behaviour, volatility, liquidity, and correlations.

• Design and evaluate systematic trading strategies using appropriate statistical methodologies.

• Perform backtesting and out-of-sample validation to assess strategy robustness.

• Investigate overfitting, transaction costs, slippage, and market impact in quantitative research.

• Develop predictive indicators and quantitative signals for systematic trading applications.

• Apply statistical techniques, time-series analysis, and machine learning where appropriate.

• Build reproducible research workflows using Python and relevant quantitative libraries.

• Collaborate with algorithmic trading engineers to translate validated research into production-ready strategies.

• Monitor deployed strategy performance and investigate deviations from expected behaviour.

• Prepare research documentation covering methodology, assumptions, limitations, and performance results.

• Evaluate strategy performance using metrics such as Sharpe ratio, drawdown, volatility, turnover, and risk-adjusted returns.

• Maintain high standards of data quality, model validation, and research reproducibility.

Requirements and Qualifications

• Master’s degree or PhD in Quantitative Finance, Mathematics, Statistics, Physics, Computer Science, Econometrics, or a related discipline; a strong bachelor’s degree with relevant professional experience may also be considered.

• At least 3 years of experience in quantitative research, systematic trading, financial modelling, or investment analytics.

• Strong proficiency in Python and quantitative computing libraries such as NumPy, pandas, SciPy, and scikit-learn.

• Solid understanding of probability theory, statistical inference, regression analysis, and time-series modelling.

• Practical knowledge of financial markets, trading instruments, and market microstructure.

• Experience designing, backtesting, and validating systematic trading strategies.

• Understanding of portfolio risk, position sizing, transaction costs, and execution constraints.

• Familiarity with SQL and large-scale financial datasets.

• Ability to communicate complex research findings clearly to technical and non-technical stakeholders.

• Strong analytical reasoning, attention to detail, and independent research capabilities.

• Experience with C++, machine learning, or high-frequency market data is advantageous.

Benefits

• Fully remote working opportunity within Estonia.

• Opportunity to contribute to quantitative research and systematic trading development.

• Access to financial market datasets and modern analytical technologies.

• Collaboration with quantitative researchers, developers, and trading professionals.

• Professional development in quantitative finance and electronic markets.

• Flexible working arrangements within an international fintech environment.

Application Instructions

Interested candidates should submit an updated CV outlining their quantitative research experience, programming capabilities, and financial market knowledge. Applicants should highlight relevant strategy research, backtesting projects, statistical models, and measurable research outcomes.

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