Browse Skills

Design and implement retrieval-augmented generation systems for legal documents with citation-safe retrieval, hallucination prevention, and privilege-aware document handling.

Senior MLOps drift detection specialist that designs production-grade monitoring pipelines with statistical tests, alerting thresholds, and automated retraining triggers.

Expert in causal graph modeling using Directed Acyclic Graphs (DAGs), structural causal models, do-calculus, and causal discovery algorithms. Guides practitioners through identification strategies, quasi-experimental designs, and implementation with DoWhy, CausalNex, and causal-learn.

Design and deploy predictive maintenance systems using edge computing, IoT sensor data, and machine learning models for anomaly detection and remaining useful life estimation in industrial environments.

Evidence-based framework that classifies AI-assisted coding practices into High-Leverage, Context-Dependent, and Dangerous tiers with a rigorous 4-criteria evaluation rubric.

Develops comprehensive data governance strategies including data catalogs, metadata management, ownership models, access policies, quality frameworks, and master data management aligned with DMBOK standards.

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

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

Conduct environmental lifecycle assessments (LCA) of products following ISO 14040/14044, covering goal definition, inventory analysis, impact assessment, and improvement recommendations for sustainable product design.

Guides you through building robust data quality frameworks — from validation rules and schema enforcement to data observability, data contracts, and remediation workflows — using industry tools like Great Expectations and Soda.

Architects multimodal AI systems that combine vision, language, and audio modalities. Designs cross-modal fusion strategies, selects appropriate models (CLIP, GPT-4V, Gemini), and builds end-to-end multimodal pipelines.

Design and implement an AI governance council structure that provides organizational oversight for responsible AI development, deployment, and monitoring aligned with emerging regulations and industry frameworks.

Expert in AI cost optimization — token efficiency, model routing, prompt caching, GPU cost management, and inference optimization strategies for LLMs and ML systems.

Configure and optimize Salesforce orgs with expert guidance on object model design, security architecture, Flow automation, reports and dashboards, and deployment best practices.

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

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.

Optimizes few-shot prompting strategies for large language models by selecting, ordering, and formatting demonstration examples that maximize output quality while minimizing token usage and cost.

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

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.

Designs and implements Monte Carlo simulations for quantitative analysis, covering probability distributions, variance reduction techniques, financial modeling (VaR, options pricing), convergence analysis, sensitivity analysis, and production-quality Python/R implementation patterns.

Expert in PyTorch production systems — neural network architecture, training loops, CNNs, distributed training, and model optimization for deployment.

Design and build production-grade internal tools, admin panels, and operational dashboards with Retool — including CRUD interfaces, approval workflows, and role-based access control.

Guides practitioners through end-to-end LoRA and QLoRA fine-tuning workflows, from dataset curation and hyperparameter selection to training optimization, evaluation, model merging, and deployment of parameter-efficient fine-tuned language models.

Design and implement cohort analyses for retention measurement, behavioral segmentation, and product analytics. Provides SQL implementations, visualization recommendations, and statistical interpretation guidance.