3. Data, Science & AI

Manages knowledge graphs to store relationships, query connected knowledge, and maintain semantic memory for autonomous coding tasks.

Automates validation of database migrations, data integrity, and query performance to ensure reliable and efficient data operations.

Provides time-series analysis and predictive modeling for business trend forecasting, incorporating social listening and signal detection.

Builds and deploys scalable machine learning systems covering data pipelines, model training, and production monitoring.

Specializes in resilient error handling for AI agent systems, detecting failures and hallucinations to enable self-healing workflows.

Configures persistent memory systems for AI applications, including LLM provider setup, knowledge graph querying, and performance optimization.

Extracts property data, including photos, valuations, and parcel details, from the Brevard County Property Appraiser GIS API.

Manages persistent cross-session memory for storing error patterns, learned solutions, and project knowledge in AI applications.

Specializes in extracting actionable insights from complex datasets through advanced analytics, pattern recognition, and multi-source data integration for strategic decision-making.

Provides multi-layer AI-driven quality assurance for code and security using LLM-as-judge and agent-based verification with 0-100 scoring.

Enables comprehensive data validation, profiling, and anomaly detection to maintain high-quality datasets for analysis and AI applications.

Configures Samsung Galaxy Watch integration with Dr. Sophia AI via Google Drive, including Health Sync setup, OAuth, and multi-user management for health data synchronization.

Tests wake word detection, STT accuracy, and conversation pipelines via virtual audio injection, covering setup, configuration, and troubleshooting.

Automates Excel data processing and manipulation using Node.js (ExcelJS, SheetJS) and Python (pandas, openpyxl) libraries.

Enables deployment, optimization, and real-time serving of machine learning models with scalable and reliable production infrastructure.

Monitors and optimizes AI agent performance through token usage tracking, latency analysis, and quality metrics to reduce costs and improve efficiency.

Transforms vague requests into production-ready, hallucination-free prompts for Claude 4.x using anti-hallucination techniques and best practices.

Provides expert guidance for designing, optimizing, and maintaining database schemas across SQL and NoSQL systems, including normalization, indexing, and GDPR compliance.

Builds reliable data pipelines with idempotent orchestration for consistent data transformation and movement.

Builds and manages end-to-end machine learning pipelines, including model versioning, feature stores, and production deployment.

Organizes object storage with lifecycle policies for efficient data retention, deletion, and management in data lake environments.

Expert guidance for implementing product analytics systems including event tracking, SDK integration, dashboard creation, and user behavior metric analysis.

Expertly designs, optimizes, and evaluates prompts for Large Language Models to enhance output quality and system performance.

Generates interactive dashboards displaying key performance indicators (KPIs) and real-time metrics for data-driven insights.