Browse Skills

Expert in MongoDB production systems — document modeling, aggregation pipelines, sharding, indexing strategy, Atlas operations, and migration from relational databases.

Design and analyze rigorous policy impact evaluations using causal inference methods including difference-in-differences, regression discontinuity, synthetic control, and propensity score matching.

Guide the end-to-end curation of high-quality datasets for machine learning. Covers data collection strategies, cleaning pipelines, annotation workflows, bias auditing, deduplication, and dataset documentation following data-centric AI principles.

Designs and enforces formal data contracts between producer and consumer teams, implementing schema governance, automated quality testing, and graduated enforcement strategies to ensure upstream data discipline.

Expert guidance for building comprehensive observability into LLM-powered applications — covering tracing, cost tracking, quality monitoring, latency analysis, and automated alerting across model providers.

Guides teams through MongoDB Atlas production deployments — cluster architecture, performance optimization, Atlas Search, security hardening, backup strategies, and cost management for cloud-native document database workloads.

Expert in Google BigQuery — SQL analytics at scale, partitioning and clustering strategies, BigQuery ML, materialized views, Dataform pipelines, cost optimization, and data governance.

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

Guides you through designing effective, insight-driven dashboards with proper KPI selection, visual encoding, and data storytelling — applying Tufte and Few principles to avoid common anti-patterns.

Design and build production-grade real-time data pipelines using Apache Kafka, Flink, Spark Streaming, and CDC patterns with exactly-once semantics and operational observability.

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

Guides geospatial data analysis including GIS fundamentals, PostGIS spatial queries, coordinate systems, geocoding, spatial indexing, and map visualization. Helps design location intelligence solutions and spatial analytics workflows.

Design rigorous, bias-minimized surveys — from research objective clarification and question writing to sampling strategy, skip logic, and analysis planning.

Designs normalized event tracking schemas for product analytics, defining event taxonomies, property standards, and validation rules to ensure consistent data collection across teams.

Build production-grade AI-powered features using the Vercel AI SDK with streaming responses, structured outputs, tool calling, and multi-provider support in Next.js applications.

Design and operate low-latency feature delivery systems for production ML, including feature store architecture, online/offline consistency, streaming pipelines, and serving infrastructure optimization.

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.

Architect production-grade AI applications with prompt chaining, agent patterns, guardrails, cost optimization, and multimodal capabilities for reliable LLM-powered systems.

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.

Optimizes ML model deployment for production inference including quantization (INT8/INT4), knowledge distillation, ONNX/TensorRT conversion, model pruning, batching strategies, and edge deployment for reducing latency and cost.

Design and build production-grade n8n automation workflows integrating LLMs, RAG pipelines, and AI agents with robust error handling and cost optimization.

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

Diagnoses and resolves neural network training failures including gradient issues, loss plateaus, overfitting, and suboptimal hyperparameters. Provides systematic debugging workflows with actionable fixes.

Designs dimensional data warehouse schemas using Kimball, Inmon, or Data Vault methodologies. Guides star/snowflake schema design, slowly changing dimensions, ETL/ELT patterns, and cloud warehouse optimization for Snowflake, BigQuery, and Redshift.