Selby Jennings
ETF Quant Researcher/Trader
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Quantitative Researcher - ETF Strategies
Overview
We are seeking a Quantitative Researcher to join a systematic investment team focused on ETF and index-based strategies. The successful candidate will be responsible for researching alpha opportunities, developing quantitative models, analysing large datasets, and enhancing portfolio construction processes across global ETF markets.
Working closely with Portfolio Managers, Traders, and Developers, the researcher will contribute to the full lifecycle of strategy development, from idea generation and signal research through to implementation and performance analysis.
Key Responsibilities
- Research and develop systematic investment strategies across ETF and index products.
- Generate and evaluate alpha signals using quantitative and statistical techniques.
- Conduct rigorous backtesting and validation of investment models.
- Analyse ETF flows, holdings, factor exposures, and market dynamics to identify trading and investment opportunities.
- Develop portfolio construction and optimisation frameworks.
- Monitor strategy performance and conduct post-trade analysis.
- Evaluate new datasets and alternative data sources for research purposes.
- Collaborate with portfolio managers and technology teams to implement and improve production strategies.
- Produce research reports and communicate findings to investment stakeholders.
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Required Skills & Experience
- Strong academic background in Mathematics, Statistics, Physics, Computer Science, Engineering, Economics, or a related quantitative field.
- Experience developing quantitative investment or trading strategies.
- Advanced Python programming skills.
- Strong knowledge of statistics, probability, econometrics, and time-series analysis.
- Experience working with large financial datasets.
- Understanding of portfolio construction, optimisation, and risk management techniques.
- Knowledge of ETFs, index methodologies, factor investing, and systematic investment approaches.
- Ability to conduct independent research and translate ideas into implementable strategies.
- Strong analytical and problem-solving skills.
Preferred Experience
- Experience researching ETF, index arbitrage, factor, or systematic equity strategies.
- Familiarity with market microstructure and execution analysis.
- Exposure to machine learning techniques and predictive modelling.
- Experience with SQL, cloud computing, and research infrastructure development.
- Understanding of ETF creation/redemption mechanisms, basket trading, and liquidity dynamics.
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Candidate Profile
The ideal candidate will possess a combination of strong quantitative research capabilities, financial market knowledge, and programming expertise. They will demonstrate intellectual curiosity, attention to detail, and a proven ability to generate investment insights through data-driven research. The role requires an individual who can independently develop research ideas while working collaboratively within a highly systematic investment environment.
Desired Skills and Experience
Strong ETF research experience, quantitative modelling, Python programming, statistical analysis, portfolio construction, factor research, risk management, and systematic alpha generation.
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