senior-data-scientist

Name: senior-data-scientist
Rating: 5 (1 reviews)
Author: timdevai

World-class senior data scientist skill specialising in statistical modeling, experiment design, causal inference, and predictive analytics. Covers A/B testing (sample sizing, two-proportion z-tests, Bonferroni correction), difference-in-differences, feature engineering pipelines (Scikit-learn, XGBoost), cross-validated model evaluation (AUC-ROC, AUC-PR, SHAP), and MLflow experiment tracking — usi

1stars

Updated 27 days ago

View on GitHub ↗License: MIT

How to add

/plugin marketplace add timdevai/proteus

The exact command may vary by repository. Check the README on GitHub.

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Drop this on your repo README

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#llm #mcp #ai #test

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Senior Data Scientist

World-class senior data scientist skill for production-grade AI/ML/Data systems.

Core Workflows

1. Design an A/B Test

import numpy as np
from scipy import stats

def calculate_sample_size(baseline_rate, mde, alpha=0.05, power=0.8):
    """
    Calculate required sample size per variant.
    baseline_rate: current conversion rate (e.g. 0.10)
    mde: minimum detectable effect (relative, e.g. 0.05 = 5% lift)
    """
    p1 = baseline_rate
    p2 = basel

[Description truncada. Veja o README completo no GitHub.]

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