3. Data, Science & AI

Analyzes iron butterfly credit spreads with ATM short straddle and OTM long strangle protection for high-IV, tight-range trading opportunities.

Calculates bond prices for fixed income securities using present value, yield-to-maturity, and market conventions with scientific computing libraries.

Provides mathematical techniques for tail risk assessment in trading using Extreme Value Theory and model validation guardrails.

Analyzes iron condor credit spreads for range-bound trading using data science tools, leveraging pandas, numpy, and matplotlib for financial strategy evaluation.

Analyzes bear-put-spread options strategies using data science tools for defined-risk bearish market positions on mid to large-cap stocks.

Analyzes protective collar strategies (long stock, long put, short call) using data science for downside hedging, income generation, and cost reduction.

Analyzes long call butterfly options spreads using data science tools for neutral market outlooks, providing risk assessment and pinning opportunity evaluation.

Applies information theory (entropy, mutual information, transfer entropy) and causal inference to develop data-driven trading signals for financial markets.

Optimizes trade execution using control theory and queueing models, analyzing order book dynamics and exchange microstructure for financial markets.

Analyzes long strangle options strategies using financial data and volatility models to evaluate high-volatility market opportunities.

Advanced mathematical optimization for trading strategies, including OCO, multi-objective, DRO, MIP, Bayesian, and convex methods, with Markowitz and Black-Litterman references.

Analyzes financial statements through ratio calculations, trend analysis, and peer comparisons using data science tools for fundamental evaluation.

Provides predictive analytics using SAP-RPT-1-OSS, a tabular foundation model, for tasks like customer churn prediction and financial anomaly detection on SAP data.

Analyzes Excel spreadsheets, generates pivot tables and charts, and performs data processing for tabular data.

Enables creation, editing, and analysis of spreadsheets with formula support, formatting, and data visualization for structured data tasks.

Enables intelligent planning and coordination of multiple specialized agents for complex multi-step tasks, supporting decomposition, dependency mapping, and dynamic execution strategies.

Analyzes GRPO training runs to diagnose issues, track Elo progression, and evaluate pipeline throughput for AI model development.

Conducts systematic ablation sweeps for GRPO training to test hypotheses and optimize hyperparameters in AI model development.

Optimizes database performance by refining SQL queries, designing efficient indexes, and managing migrations to resolve slow queries and N+1 issues.

Optimizes prompts for LLMs and AI systems to enhance performance, build AI features, and refine system instructions using proven prompt engineering techniques.

Stores and manages user preferences learned through slipstream's data processing system.

Extracts and structures email content from .eml files, including threads and attachments, for AI processing.

Expert in executing SQL queries and BigQuery operations to derive actionable data insights for analytical decision-making.

Manages context across multiple AI agents and long-running tasks, preserving state for complex workflows and large context windows (over 10k tokens).