3. Data, Science & AI

Transforms raw data into compelling narratives using visualization and persuasive structure for stakeholder presentations and executive reports.

Calculates portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown for risk monitoring and limit implementation.

Provides best practices for constructing production-ready Apache Airflow DAGs, covering operators, sensors, testing, and deployment for data pipelines and workflow orchestration.

Designs LLM applications using LangChain framework with agent architectures, memory management, and tool integration patterns for complex AI workflows.

Builds end-to-end MLOps pipelines for data preparation, model training, validation, and production deployment, automating the machine learning lifecycle.

Specializes in dynamic context management for AI systems using vector databases, knowledge graphs, and multi-agent orchestration to enhance LLM-based applications.

Builds production-ready LLM applications, advanced RAG systems, and intelligent agents with vector search and multimodal capabilities.

Provides advanced data analysis, machine learning modeling, and statistical insights for business intelligence and predictive analytics.

Builds robust backtesting systems for trading strategies, handling look-ahead bias, survivorship bias, and transaction costs to validate algorithmic trading performance.

Optimizes LLM performance and output quality using advanced prompt engineering techniques for production environments.

Expert in designing scalable database architectures, including schema modeling, technology selection (SQL/NoSQL/TimeSeries), and performance optimization for greenfield and existing systems.

Optimizes cloud-native database performance using advanced SQL techniques, data modeling, and OLTP/OLAP systems for complex analytical workloads.

Enables statistical analysis, backtesting, and portfolio optimization for financial modeling and risk assessment using quantitative methods.

Enables safe, zero-downtime schema evolution for relational databases using SQL-based migration strategies.

Creates and manages agent definitions for code-forge using YAML frontmatter and Markdown format, enabling AI agent configuration and instruction setup.

Assists in designing database schemas, creating tables, and planning data relationships for efficient data management and application development.

Converts natural language data queries into executable SQL, enabling non-technical users to interact with databases.

Enables database querying, schema exploration, and data analysis across multiple systems including PostgreSQL, MySQL, and MongoDB.

Generates query-agnostic analytics to model adversary behavior by translating investigative intent into schema-grounded analytic definitions for threat hunting.

Extracts and analyzes text, tables, and structured data from PDF documents for data processing and analysis.

Builds stateful AI agents with persistent state, scheduling, and communication features using Cloudflare Agents SDK.

Creates AntV Infographic DSL syntax for data visualizations, handling template selection, data structuring, and theming.

Comprehensive guide for AntV L7 geospatial visualization library, enabling interactive maps, geographic data dashboards, and spatial data processing.

Provides advanced financial modeling tools including DCF, Monte Carlo simulations, and scenario planning for investment decision analysis.