Quantitative Finance Forecasting Analyst

Quantitative model review

Evaluate predictive models and financial reasoning produced by AI. The work focuses on whether inputs, logic, and assumptions support the conclusions.

• Review quantitative output and examine the model logic behind it.
• Validate forecasting drivers and identify errors, inconsistencies, or unrealistic assumptions.
• Summarize expected trends and performance scenarios in organized written form.
• Detect anomalies in structured financial and statistical datasets.
• Record findings using the evaluation frameworks provided for AI training.
• Manage independent assignments asynchronously.

Required background

A strong quantitative finance, statistics, econometrics, or data analysis background is required. You should be able to interrogate model logic, recognize weak assumptions, and interpret complex numerical results.

The role calls for systematic, careful review and concise explanations of technical findings. Reliable independent delivery and comfort working with structured data are essential.

Useful experience

Python, R, MATLAB, or other modeling tools are helpful. Financial models, forecasting, risk analysis, investment research, quantitative research, and academic or buy-side and sell-side finance experience are also relevant.

Previous AI evaluation or data labeling work is welcome.

Contract scope

The hourly contract is fully remote and flexible, allowing you to organize work around your schedule. Continued assignments or a contract extension may be available as new projects begin.