Quantitative Financial Analyst – AI Focus
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
Apply tot his job
Apply To this Job
• 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
Apply tot his job
Apply To this Job