I will research, build and validate a quantitative ML hypothesis for financial or crypto markets.
I can help transform a market idea into a measurable research problem: define the target, prepare historical data, engineer features, build baseline and ML models, design time-aware validation and analyze whether the signal has real predictive value.
My focus is not on producing a visually impressive backtest, but on finding whether the hypothesis survives realistic validation.
Work may include:
• Alpha / signal research
• Target and feature design
• Time-series ML
• Walk-forward / pretest validation
• Threshold analysis
• Precision / recall / PR-AUC analysis
• Regime analysis
• Overfitting and leakage checks
• Research report and reusable Python code
No guaranteed trading returns or profitability claims.
