Browse Skills

Design comprehensive evaluation systems for LLMs and AI applications, covering automated metrics, human evaluation protocols, LLM-as-a-judge pipelines, and CI/CD-integrated regression testing.

Expert analytics engineering skill for dbt Core/Cloud — guides you through SQL-based data modeling with staging/intermediate/mart layers, dimensional modeling (Kimball methodology), incremental models, SCD Type 2 snapshots, comprehensive testing strategies, Jinja macros, dbt packages, and warehouse-specific optimization for Snowflake, BigQuery, and Redshift.

Prepare research outputs for public sharing and long-term preservation with FAIR-compliant data packaging, reproducible environments, proper licensing, and repository publication strategies.

Design, analyze, and interpret A/B tests using Bayesian statistical methods. Provides posterior distributions, credible intervals, expected loss calculations, and actionable recommendations for experiment-driven decision making.

Designs, builds, and optimizes complex multi-step Zapier workflows connecting multiple SaaS applications, with branching logic, error handling, sub-Zaps, and task optimization for production-grade business automation.

Designs optimal text chunking strategies for Retrieval-Augmented Generation (RAG) systems, balancing chunk size, semantic coherence, retrieval precision, and generation quality across diverse document types.

Designs measurable outcome indicator frameworks for social impact programs, including theories of change, logic models, SMART indicators, and results-based monitoring systems.

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

Design and calibrate risk scoring systems that identify at-risk individuals within cohorts — enabling early interventions for student retention, customer churn prevention, patient readmission, and other predictive analytics use cases.

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.

Reduces LLM API costs through systematic token optimization — prompt compression, caching strategies, model routing, and batch processing — while maintaining output quality across OpenAI, Anthropic, and open-source models.

Design and build custom, interactive data visualizations using D3.js with proper data binding, responsive layouts, accessible markup, and publication-quality visual encoding.

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.

Design, optimize, and operate ClickHouse OLAP clusters for real-time analytics on billions of rows with sub-second query performance.

Design domain-oriented, decentralized data architectures using data mesh principles including data-as-a-product, self-serve infrastructure, and federated computational governance.

Design and build reliable API integrations in Make (formerly Integromat) using HTTP modules, OAuth flows, pagination handling, and advanced error recovery patterns.

Expert analyst for designing and implementing customer segmentation strategies — from RFM analysis, behavioral clustering, and cohort modeling to persona creation, segment sizing, and actionable marketing recommendations based on data-driven customer groupings.

Create publication-quality static figures with Matplotlib and interactive web-ready visualizations with Plotly, guided by visual perception research and data storytelling principles.

Designs and implements enterprise skills taxonomies and competency frameworks that enable skills-based workforce planning, internal mobility, gap analysis, and learning path mapping using validated I/O psychology methodologies.

Guides the design of reinforcement learning systems including policy selection (PPO, SAC, DQN), environment design, reward shaping, exploration strategies, multi-agent configurations, and sim-to-real transfer for robotics and game AI.

Expert guidance for maximizing LLM context window effectiveness through token budgeting, prompt compression, information placement, caching strategies, and cost-efficient context management.

Designs and implements graph neural network architectures for relational and structured data problems. Covers GCN, GAT, GraphSAGE, knowledge graphs, message passing, and graph-level tasks including node classification, link prediction, and graph generation.

Expert guidance for building and optimizing Apache Spark data processing pipelines, from PySpark development to cluster tuning and lakehouse architecture.

Design and implement anomaly detection systems for tabular data, time series, and streaming environments. Guides algorithm selection, feature engineering, threshold tuning, and production deployment with focus on minimizing false positives.