Browse Skills

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

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 and implement automated data quality frameworks using Great Expectations, dbt tests, data contracts, and observability platforms to ensure trustworthy data pipelines.

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.

Design effective chain-of-thought prompting strategies that elicit step-by-step reasoning from large language models for complex problem-solving, analysis, and decision-making tasks.

Design BI architectures with semantic layers, dimensional models, self-service analytics, KPI frameworks, and modern data stack patterns using dbt, Looker, Metabase, and Tableau.

Transform data into compelling visual narratives using chart type selection, Tufte principles, color theory, annotation strategies, and audience-adapted presentation-ready outputs.

Guides the creation of high-impact Tableau dashboards with advanced calculated fields, LOD expressions, performance optimization, and data storytelling best practices.

Guide systematic exploratory data analysis workflows — from initial profiling through distribution analysis, correlation discovery, and hypothesis generation — using statistical rigor and effective visualization.

Designs and implements time series forecasting solutions — from data preprocessing and stationarity testing through model selection (ARIMA, Prophet, LSTM, Transformer-based), evaluation with proper temporal cross-validation (MAPE, RMSE, MASE), to production deployment with ensemble approaches and drift monitoring.

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.

Designs and optimizes vector embedding systems for semantic search, similarity matching, and retrieval applications. Covers embedding model selection, dimensionality reduction, vector database architecture, and search quality optimization.

Expert in AI safety evaluation — adversarial testing, jailbreak prevention, prompt injection defense, bias detection, and safety benchmarking for LLMs and AI systems.

Design and adapt survey instruments for cross-cultural and multinational research. Covers translation-backtranslation protocols, measurement invariance testing, cultural response style mitigation, and construct equivalence validation following ITC guidelines and established psychometric standards.

Rigorous causal inference methods for isolating the true impact of price changes on demand, revenue, and customer behavior using econometric techniques, DAG-based reasoning, and experimentation design.

Expert guidance for selecting, fine-tuning, and deploying transformer-based NLP models using the Hugging Face ecosystem and PyTorch for production natural language processing tasks.

Designs multi-stage ML model deployment pipelines with automated rollback triggers, canary releases, and shadow deployments to ensure safe, reversible model updates in production.

Provides expert guidance on transformer neural network architectures, including attention mechanisms, positional encoding schemes, encoder-decoder design patterns, tokenization strategies, and context window optimization for building and understanding modern LLMs.

Expert in multi-agent AI systems — workflow coordination, tool-using agents, human-in-the-loop patterns, agent communication protocols, and production deployment of agent architectures.

Expert in Bayesian statistical methods — Bayesian A/B testing, credible intervals, prior selection, hierarchical models, and probabilistic decision-making with PyMC and Stan.

Isolate the true causal effect of price changes on demand, revenue, and profit using rigorous econometric methods including difference-in-differences, instrumental variables, and synthetic control.

Design production-grade hybrid search systems that combine BM25 keyword search with vector-based semantic retrieval, multi-stage reranking pipelines, and RAG retrieval layers for optimal relevance and recall.

Designs retention measurement systems, builds churn prediction models, and creates data-driven intervention strategies that measurably reduce customer churn across SaaS, e-commerce, and subscription businesses.

Design data activation pipelines that sync analytical data from cloud data warehouses back into operational SaaS tools like CRMs, marketing platforms, and support systems.