Quantitative Researcher [Based in Cayman Islands]

*** Relocation Opportunity - Cayman Islands **** We are seeking a Quantitative Researcher to join an financial services team and support the development of quantitative research, investment strategies, portfolio analytics, and data-driven decision-making. The successful candidate will apply statistical, mathematical, and computational techniques to financial markets and investment data. This role will work closely with Portfolio Managers, Investment Analysts, and other members of the investment team to identify investment opportunities, develop quantitative models, evaluate portfolio risks, and improve investment processes. Key Responsibilities Conduct quantitative research across equities, fixed income, credit, derivatives, and other financial markets. Develop and test quantitative investment models, signals, factors, and systematic strategies. Analyze large datasets to identify trends, patterns, relationships, and potential investment opportunities. Perform statistical analysis, backtesting, and performance attribution of investment strategies. Develop tools and models to support portfolio construction, asset allocation, risk management, and security selection. Work with Portfolio Managers and investment professionals to translate investment ideas into quantitative frameworks. Build and maintain research datasets and analytical processes. Develop predictive models using statistical and machine-learning techniques where appropriate. Analyze portfolio and market data to identify sources of risk, return, volatility, and correlation. Conduct scenario analysis, stress testing, and other quantitative assessments. Monitor the performance and robustness of quantitative models and investment strategies. Automate recurring research, reporting, and analytical processes. Present quantitative findings and investment research to senior investment professionals. Maintain accurate documentation of models, methodologies, assumptions, and research results. Stay current with developments in quantitative finance, financial markets, statistical modelling, and data science. Technical Requirements Strong programming skills in Python, with experience using libraries such as Pandas, NumPy, SciPy and/or Scikit-learn. Strong knowledge of statistics, probability, econometrics, and quantitative modelling. Experience working with large financial datasets. Strong SQL and database skills. Experience with financial modelling, time-series analysis, and statistical analysis. Familiarity with quantitative portfolio construction and risk-management techniques. Experience conducting investment strategy research and backtesting. Knowledge of financial markets, securities, and investment products. Experience with data visualization and analytical tools. Knowledge of machine learning and/or alternative data would be an advantage. Education & Experience Bachelor's or Master's degree in Mathematics, Statistics, Economics, Finance, Computer Science, Engineering, Physics, or a related quantitative discipline. Typically 2–7 years of experience in quantitative research, investment research, quantitative finance, trading, risk analytics, or a related field. Experience within an investment management firm, hedge fund, asset manager, proprietary trading firm, investment bank, or similar financial institution is preferred. CFA, FRM, Master's, or PhD qualification would be considered an asset.

The role involves developing quantitative investment models, signals, and systematic strategies across various financial markets. The researcher will analyze large datasets to identify investment opportunities and perform risk assessments and performance attribution.

Candidates need a quantitative degree and 2-7 years of experience in quantitative research or finance, preferably within a hedge fund or investment bank. Proficiency in Python, SQL, and statistical modeling is required.

• Data visualizationPreferred
• SQLPreferred
• Machine learningPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Python
• Pandas
• NumPy
• SciPy
• Scikit-learn
• SQL
• Quantitative Modeling
• Statistical Analysis
• Econometrics
• Backtesting
• Portfolio Construction
• Risk Management
• Time-series Analysis
• Machine Learning
• Data Visualization
• Financial Modeling

• Finance & Accounting
• Data & Analytics
• Science & Research
• Technology
• Engineering

Minimum education

Bachelor’s degree

Minimum experience

2+ years

Apply by

Sep 16, 2026

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available