3. Data, Science & AI

Designs and manages multi-agent systems using collaboration patterns, hierarchical structures, and swarm intelligence for autonomous workflow orchestration.

Designs real-time data processing systems with windowing and watermarking for accurate event-driven analytics.

Comprehensive tool for creating, editing, and analyzing spreadsheets with formula support, formatting, data analysis, and visualization across multiple spreadsheet formats.

Manages Qdrant Cloud collections for RAG systems, handling vectorization of textbook chapters and metadata tagging to enhance retrieval accuracy.

Performs statistical analysis, predictive modeling, and machine learning to transform data into actionable business insights through data storytelling.

Provides SQL development, database design, and optimization services across PostgreSQL, MySQL, SQL Server, and Oracle platforms.

Personalizes textbook content into adaptive learning experiences using RAG and a 10-dimensional user profile.

Specializes in designing and managing real-time data pipelines using Apache Kafka, including event streaming, Kafka Connect, and schema management.

Triggers on Codex-related requests to facilitate iterative AI-to-AI discussions and collaboration with the Codex AI model.

Enables high-performance CSV data processing, cleaning, and transformation using Python and DuckDB for efficient tabular data management.

Models relationships and executes graph queries in graph databases, enabling efficient data navigation and relationship analysis.

Guides on selecting optimal charts, encoding data hierarchies, and ensuring accessibility and performance in data visualizations.

Provides business intelligence analysis, SQL querying, and data visualization to transform raw data into strategic business insights.

Performs quantitative financial analysis, algorithmic trading strategy development, and statistical modeling using Python and machine learning.

Coordinates 100+ agents across distributed systems using hierarchical control, dynamic scaling, and intelligent resource allocation for complex AI orchestration.

AI-powered tool that learns from user feedback to extract patterns and provide personalized learning recommendations.

Manages versioned features for consistent offline training and online model serving in machine learning systems.

Creates and manages data catalogs for organizing metadata, tracking data lineage, and enabling data discovery within an organization.

Manages SQLite database schemas and structure using better-sqlite3 for the 5BulletMethod application.

Generates customizable parabola plots in R for quadratic function analysis, mathematical visualization, and educational demonstrations.

Defines memory retrieval and storage protocol for AI agents, making memory core to reasoning from session start.

Enables users to interact with multiple LLM models via OpenRouter, compare responses, track costs, and optimize model selection for efficiency.

Analyzes slow database queries and provides actionable index recommendations to improve performance.

Ensures bit-identical training results between gradient accumulation and standard batching for reproducibility debugging in machine learning model training.