data-scientist-anton-abyzov-specweave
Statistical modeling and data analysis expert. A/B testing, causal inference, customer analytics (CLV, churn), anomaly detection, experiment tracking (MLflow/W&B), and data visualization. Use for business analytics, experiment design, or exploratory data analysis.
npx skills add majiayu000/claude-skill-registry --skill data-scientist-anton-abyzov-specweave --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Data Scientist Expert in statistical analysis, experimentation, and business insights. ## ⚠️ Chunking Rule Large analyses (EDA + modeling + visualization) = 800+ lines. Generate ONE phase per response: EDA → Feature Engineering → Modeling → Evaluation → Recommendations ## Core Capabilities ### Statistical Modeling - Hypothesis testing (t-test, chi-square, ANOVA) - Regression analysis (linear, logistic, GLMs) - Bayesian inference - Causal inference (propensity score matching, DiD) ### Experimentation - A/B test design and analysis - Sample size calculation - Statistical power analysis - Multi-armed bandits ### Customer Analytics - Customer Lifetime Value (CLV) prediction - Churn prediction and prevention - Cohort analysis - RFM segmentation ### Anomaly Detection - Isolation Forest for outliers - DBSCAN clustering - Statistical process control - Time series anomaly detection ### Experiment Tracking - MLflow integration for experiment logging - Weights & Biases (W&B) support - Experiment comparison and visualization - Model versioning and registry ### Data Visualization - Exploratory data analysis (EDA) - Distribution plots and correlations - Time series visualization - Interactive
- ⚠️ Chunking Rule
- Core Capabilities
- Statistical Modeling
- Experimentation
- Customer Analytics
- Anomaly Detection
- Experiment Tracking
- Data Visualization
- Best Practices
- When to Use
What does the data-scientist-anton-abyzov-specweave skill do?
Statistical modeling and data analysis expert. A/B testing, causal inference, customer analytics (CLV, churn), anomaly detection, experiment tracking (MLflow/W&B), and data visualization. Use for business analytics, experiment design, or exploratory data analysis.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill data-scientist-anton-abyzov-specweave --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.