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senior-data-scientist

World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.

67

1.41x
Quality

60%

Does it follow best practices?

Impact

68%

1.41x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./bundled/skills/senior-data-scientist/SKILL.md
SKILL.md
Quality
Evals
Security

Evaluation results

69%

33%

A/B Test Design for Checkout Funnel Optimization

Experiment design with provided scripts

Criteria
Without this skill
With this skill

Uses experiment_designer script

0%

100%

Correct script flags

0%

100%

Power analysis script has type hints

100%

100%

Alpha = 0.05 used

100%

100%

Power = 0.80 used

100%

100%

Monitoring plan present

100%

100%

MLflow or W&B mentioned

0%

0%

Uptime/error rate target

0%

0%

Latency SLO referenced

0%

100%

Scikit-learn or statsmodels used

0%

0%

Batch processing mentioned

0%

0%

60%

4%

Customer Churn Prediction Feature Pipeline

Feature engineering pipeline with reliability patterns

Criteria
Without this skill
With this skill

Uses feature pipeline script

0%

0%

Correct script flags

0%

0%

Type hints in pipeline

100%

100%

Batch processing design

75%

100%

Retry logic present

0%

0%

Circuit breaker or failure design

42%

57%

Data quality validation

100%

100%

Comprehensive tests written

100%

100%

Pandas or NumPy used

100%

100%

Comprehensive logging

100%

100%

10x scalability noted

0%

0%

Feature catalog complete

100%

100%

77%

8%

Production Readiness Review for Credit Risk Model

Model evaluation with security and monitoring

Criteria
Without this skill
With this skill

Uses model eval script

0%

0%

Correct script flags

0%

0%

PII anonymization addressed

100%

100%

Data encryption addressed

100%

100%

GDPR/CCPA compliance

100%

100%

Latency SLOs specified

100%

100%

Error rate target specified

100%

100%

MLflow or W&B for tracking

62%

100%

Canary or feature flag deployment

100%

100%

Type hints in eval script

100%

100%

Comprehensive logging in code

0%

100%

SSN/PII not logged raw

100%

100%

Repository
foryourhealth111-pixel/Vibe-Skills
Evaluated
Agent
Claude Code
Model
Claude Sonnet 4.6

Table of Contents

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