Quantitative Researcher, iSAM Vector

Quantitative Researcher

We are seeking a highly motivated Quantitative Researcher to join iSAM Vector, a systematic fund serving institutional investors. You will contribute to the research, development and monitoring of systematic trading strategies across global markets and support the full research lifecycle.

Responsibilities

• Develop new signals and research ideas across global markets, from initial research questions through to testing, validation and implementation.
• Enhance existing systematic strategies through signal refinement, model improvements and rigorous empirical testing.
• Analyze financial market data to identify, test and validate new investment ideas.
• Research and backtest systematic signals across markets, instruments and time horizons.
• Support the development of portfolio construction, risk management and implementation techniques.
• Build an understanding of how research ideas are translated into live trading strategies, from signal design through to implementation and monitoring.
• Work with researchers and technologists to translate research ideas into robust production ready trading signals.
• Develop research tools, datasets and analytical infrastructure to improve the research process.
• Communicate research findings clearly to technical and non technical stakeholders.

Qualifications

• A strong academic background in a quantitative discipline such as mathematics, statistics, physics, engineering, computer science, economics, or finance.
• Strong programming skills, preferably in Python, with experience using data analysis libraries such as Pandas and NumPy.
• A solid understanding of statistics, probability, time series analysis, optimisation or machine learning.
• Interest in financial markets, systematic investing and empirical research.
• Ability to work with large, complex datasets and draw robust conclusions from noisy data.
• Ability to work through a full research pipeline, including data analysis, hypothesis testing, signal construction, robustness checking and backtesting.
• A rigorous approach to research design, backtesting and model validation.

Useful but not Essential

• Prior experience in quantitative research, systematic trading, asset management or a research focused data science role.
• Familiarity with portfolio construction, risk management, transaction cost analysis or signal research.
• Experience with futures, FX, equities, rates, commodities or other liquid markets.
• Exposure to machine learning, econometrics or alternative datasets.

Personal Attributes

• Strong communication skills and the ability to explain technical ideas clearly.
• Curiosity, intellectual honesty and a willingness to challenge assumptions.