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,...
40 results
(77.1ms)
page 2 / 2
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,...
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure,...
test-data-management
0.17
Strategic test data generation, management, and privacy compliance. Use when creating test data, handling PII, ensuring GDPR/CCPA compliance, or scaling data generation for realistic testing scenarios.
data-researcher
0.17
Data discovery and analysis specialist focused on extracting actionable insights from complex datasets, identifying patterns and anomalies, and transforming raw data into strategic intelligence....
data-governance
0.17
Use when implementing data governance frameworks, building data catalogs, establishing data lineage, defining data quality rules, or setting up data stewardship programs - covers metadata...
test-data-generation
0.17
Generate realistic, consistent test data using factories, fixtures, and fake data libraries. Use for test data, fixtures, mock data, faker, test builders, and seed data generation.
synthetic-data
0.17
Patterns for generating synthetic data for ML training, testing, and privacy. Covers LLM-based generation, tabular synthesis, and quality validation. Use when "synthetic data, generate training...
design-engineering
0.17
Help users understand and build design engineering capabilities. Use when someone is creating a design engineering function, hiring design engineers, or bridging the gap between design and...
Guide for reverse engineering tools and techniques used in game security research. Use this skill when working with debuggers, disassemblers, memory analysis tools, binary analysis, or decompilers...
discover-engineering
0.16
Automatically discover software engineering practice skills when working with engineering practices. Activates for engineering development tasks.
Build robust processes for data cleaning, missing value imputation, outlier handling, and data transformation for data preprocessing, data quality, and data pipeline automation
spark-engineer
0.16
Use when building Apache Spark applications, distributed data processing pipelines, or optimizing big data workloads. Invoke for DataFrame API, Spark SQL, RDD operations, performance tuning,...
spark-engineer
0.16
Use when building Apache Spark applications, distributed data processing pipelines, or optimizing big data workloads. Invoke for DataFrame API, Spark SQL, RDD operations, performance tuning,...
engineering-culture
0.16
Help users build strong engineering culture. Use when someone is improving developer experience, fostering technical excellence, designing engineering practices, or scaling an engineering organization.
sre-engineer
0.16
Expert Site Reliability Engineer specializing in SLOs, error budgets, and reliability engineering practices. Proficient in incident management, post-mortems, capacity planning, and building...
engineering-manager
0.16
Engineering Manager skill for team leadership, 1-on-1s, performance reviews, hiring, career development, and technical team management. Use when managing engineering teams, conducting performance...
data-journalism
0.16
Data journalism workflows for analysis, visualization, and storytelling. Use when analyzing datasets, creating charts and maps, cleaning messy data, calculating statistics, or building data-driven...
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.