Ricardo Moncayo

What I do: Review your data split and validation strategy Detect potential data leakage Check for overfitting / unstable performance Assess metric interpretation Provide 3–5 concrete improvement actions Who this is for: Early-stage startups building predictive models Founders using ML but unsure about robustness Researchers preparing for submission CTOs wanting a second technical opinion

What I do: -Evaluate cross-validation design -Assess generalization strategy -Review resampling framework -Suggest robust validation improvements -Provide short technical report Industries where this fits well: -Healthtech -fintech risk modeling -Industrial predictive maintenance - Energy load forecasting AI-based SaaS tools Computer vision startups Biotech / diagnostics Climate modeling startups

What I do: - Reliability diagnostics - Variance & instability assessment - Stress-testing framework - Confidence interval validation - Failure mode analysis Industries where this is valuable: - Medical AI / digital health - Financial risk scoring - Insurance underwriting models - Autonomous systems - Industrial safety systems - Environmental risk modeling - Pharma data science teams

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