Browse Skills

Master GA4 exploration reports to extract actionable insights from funnel analysis, path exploration, cohort retention, and segment comparisons for data-driven decisions.

Analyzes and optimizes SQL queries for maximum performance, covering execution plan interpretation, indexing strategies (B-tree/GIN/GiST), window functions, CTEs, materialized views, partitioning, and PostgreSQL-specific optimization techniques.

Design rigorous A/B experiments, calculate sample sizes, select statistical methods, analyze results with proper significance testing, and deliver actionable recommendations.

Design, tune, and evaluate search systems for maximum relevance using BM25, hybrid retrieval, learning-to-rank, and neural re-ranking with rigorous offline and online evaluation frameworks.

Analyzes conversion funnels across acquisition, activation, and monetization stages, identifying drop-off points, statistical significance of changes, and optimization opportunities using event data.

Design AI agent systems with precisely calibrated human oversight, mapping every action to the right autonomy level — from fully automatic to synchronous approval — using established frameworks for trust calibration, escalation policies, and audit trail architecture.

Designs automated machine learning pipelines for model selection, hyperparameter optimization, and neural architecture search. Covers AutoML frameworks (Optuna, Ray Tune, Auto-sklearn), search strategies, and production integration.

Design rigorous geographic experiments (geo-lift tests) to measure the true incremental impact of marketing campaigns, product launches, and pricing changes using causal inference methods.

Designs comprehensive evaluation frameworks for LLM and AI systems, combining automated metrics (BLEU, ROUGE, BERTScore), LLM-as-judge patterns (G-Eval), RAG evaluation (RAGAS), standard benchmarks (MMLU, HumanEval), safety evaluations, and A/B testing methodologies into production-ready evaluation pipelines.

Designs robust ETL and ELT data pipelines with focus on idempotency, incremental loading, data lineage, and orchestration. Guides implementation with Apache Airflow, dbt, and modern data stack tools.

Designs comprehensive LLM prompt evaluation frameworks with tailored metric suites, automated eval pipelines, A/B testing methodology, red-teaming protocols, and regression detection systems using industry-standard tools like RAGAS, DeepEval, and promptfoo.

Design and implement safety, quality, and compliance guardrail systems for LLM-powered applications, covering input validation, output screening, prompt injection defense, PII protection, and regulatory compliance mapping.

Expert in causal inference methods — causal graphs (DAGs), difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, and policy impact evaluation.

Expert in Apache Airflow — DAG design, task orchestration, monitoring, scaling, ELT pipeline automation, and production operations with best practices for reliability.

Expert in Python-based data analysis — Pandas, NumPy, exploratory data analysis, statistical profiling, data cleaning, and visualization for business insights.

Designs privacy-preserving distributed machine learning systems using federated learning. Covers federated averaging, differential privacy, secure aggregation, communication efficiency, and compliance with privacy regulations.

Guides the design, development, testing, and deployment of custom PostgreSQL extensions using C, Rust (pgrx), or trusted languages (pg_tle) with proper type systems, index integration, and upgrade paths.

Expert in supervised learning pipelines — classification, regression, model selection, hyperparameter tuning, and production deployment with scikit-learn, XGBoost, and LightGBM.

Master XGBoost for tabular data problems including hyperparameter optimization, feature engineering, SHAP-based interpretability, and production deployment with drift monitoring.

Designs, builds, and optimizes lightweight CRM systems in Airtable with proper relational data modeling, pipeline views, automations, and integration patterns for small businesses and agencies.

Conducts comprehensive bias audits and ethical assessments of AI/ML systems, applying fairness metrics, regulatory frameworks (NIST AI RMF, EU AI Act), and structured impact assessments to identify and mitigate algorithmic harms.

Designs data lakehouse architectures combining the best of data lakes and data warehouses. Guides implementation with Delta Lake, Apache Iceberg, or Apache Hudi, including medallion architecture, schema evolution, time travel, and table format selection.

Designs robust data pipelines covering ETL/ELT patterns, orchestration (Airflow/Dagster/Prefect), data quality validation, lineage tracking, idempotency, streaming vs batch architecture, and data lakehouse design for production workloads.

Expert guidance on designing, building, and querying knowledge graphs using ontology engineering, graph databases, NLP-based construction pipelines, and LLM/GraphRAG integration patterns.