The key responsibilities will include developing and maintaining an R-based factor back-testing module, designing and implementing quantitative factor models, and conducting back-tests to evaluate investment strategies and performance. The role will involve applying commercial modeling techniques, analyzing data, validating model outputs, and identifying opportunities for improvement. The individual will be expected to work independently, troubleshoot technical issues, and deliver high-quality results with minimal supervision. They will also support the teams potential future transition from R to Python and help mentor junior analysts by sharing best practices and technical knowledge.
Key competencies
- Strong hands-on experience with R programming, particularly for quantitative finance and statistical modeling.
- Proven experience developing and implementing factor-based investment models.
- Expertise in factor back-testing, including strategy construction, performance analysis, and model validation.
- Strong knowledge of financial markets, investment strategies, and quantitative research methodologies.
- Ability to work independently, troubleshoot issues, and deliver solutions with minimal training or supervision.
- Strong analytical, problem-solving, and data interpretation skills, with high attention to detail.
- Degree in a quantitative field from a top-tier university
- Demonstrated ability to work both independently and with a team
- Solid communications skills both oral and written
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