Job Description
- Job Description:
- Design and document systematic investment workflows (factor models, back-testing, portfolio construction, VaR, stress testing).
- Develop evaluation criteria and benchmark solutions to assess AI performance on quantitative finance tasks.
- Review and validate AI-generated outputs for statistical accuracy, modeling soundness, and risk logic.
- Curate and structure high-quality financial and market data for model training and testing.
- Provide feedback to improve AI reasoning in derivatives modeling, risk assessment, and alpha generation.
- Requirements:
- 3+ years of experience as a Quantitative Analyst, Quantitative Researcher, Risk Manager, Systematic Portfolio Manager, or Derivatives Trader.
- Strong background in statistics, probability, time-series analysis, and financial modeling.
- Proficiency in Python and experience working with large financial datasets.
- Hands-on experience with systematic strategies, back-testing frameworks, derivatives (options, futures, swaps), and risk models (VaR, stress testing).
- High analytical mindset, attention to detail, and ability to clearly explain quantitative reasoning.
- Benefits:
- Flexible work arrangements
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