A financial technology and trading operation in Estonia is looking for a talented Quantitative Strategist to develop systematic approaches to market analysis and trading. This role is research-oriented and combines quantitative modelling, statistical research, financial-market analysis, and strategy development.

The successful candidate will investigate market behaviour, formulate quantitative hypotheses, develop systematic strategies, and evaluate their performance using historical and live data. You will work alongside traders, software engineers, researchers, and risk specialists to transform quantitative ideas into robust analytical and trading solutions.

Responsibilities

• Research systematic trading opportunities across relevant financial markets.
• Develop quantitative hypotheses based on market data, financial theory, and observed market behaviour.
• Design statistical and mathematical models for forecasting, signal generation, and strategy evaluation.
• Build and test systematic trading strategies using historical datasets.
• Conduct rigorous backtesting and performance analysis.
• Evaluate strategy performance across different market regimes and volatility environments.
• Investigate transaction costs, liquidity constraints, slippage, and other execution considerations.
• Develop factor-based, statistical, or machine-learning approaches where appropriate.
• Analyse relationships between financial instruments and identify potential predictive signals.
• Work closely with developers to translate research models into production-ready systems.
• Collaborate with traders and risk specialists to evaluate practical strategy considerations.
• Monitor live strategy performance and investigate deviations from expected behaviour.
• Document research findings, assumptions, methodologies, and model limitations.
• Continuously refine quantitative strategies based on empirical evidence and new market information.

What We Are Looking For

• Experience in quantitative research, systematic trading, financial engineering, or a closely related discipline.
• Strong understanding of probability, statistics, time-series analysis, and optimisation.
• Strong programming skills, particularly Python; experience with C++, R, or SQL is beneficial.
• Practical experience with financial datasets and quantitative research environments.
• Understanding of market microstructure, execution, liquidity, and transaction costs.
• Experience conducting backtests and evaluating strategy robustness.
• Strong mathematical reasoning and ability to investigate complex problems independently.
• Ability to distinguish genuine statistical relationships from overfitted or unreliable signals.
• Strong communication skills and ability to collaborate with multidisciplinary teams.
• Advanced degree in mathematics, statistics, computer science, physics, engineering, economics, or a comparable quantitative field is advantageous.

Ideal Candidate

The ideal candidate is research-driven, intellectually curious, and evidence-oriented. You should enjoy testing ideas rather than relying on assumptions and be comfortable challenging existing models when the data suggests a different conclusion.

You should also understand that a successful quantitative strategy requires more than a strong backtest. Robustness, execution, liquidity, risk, data quality, and operational reliability must all be considered before research can become a practical trading solution.

Opportunity

This position offers meaningful exposure to systematic trading research and modern financial technology. It is particularly suited to a quantitative professional who wants to work at the intersection of mathematics, programming, financial markets, and algorithmic strategy development within Estonia.

Are you interested in this position?

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

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