Senior Quantitative Developer and Equity Derivatives Trader

I develop and maintain large-scale financial datasets integrating market, portfolio, and risk information for reporting and decision-making. I design automated Python, SQL Server, and REST API pipelines to collect, clean, standardize, and govern multi-source financial data.

I build statistical and econometric engines for scenario analysis, stress testing, volatility surfaces, and pricing vanilla and exotic options. I also develop sequential backtesting and data-analysis tools for options and cash-equities strategies across multiple market conditions.

I architect and own an in-house equity analysis and risk platform, using Python, FastAPI, Pandas, and NumPy for authenticated quantitative REST services and React/Angular for the web interface. I manage Git-based delivery, automated testing, staged Azure deployments, and support daily pricing, screening, and risk monitoring for structuring, trading, and portfolio-management desks.

I conducted quantitative analysis of financial time series and market data to support derivatives pricing and risk decisions. I built Python- and R-based frameworks for statistical analysis, simulation, backtesting, and strategy evaluation under varied market scenarios.

I produced reports and presentations on market trends, insights, and risk factors for stakeholders. I automated structured-product systems, models, and workflows, increasing desk operations from 15 to 200 per day.

I traded and structured vanilla and exotic options across equities, commodities, and FX, contributing to growth in derivatives assets under management from BRL 500 million to BRL 10 billion.

I developed statistical models for credit risk assessment using structured financial datasets. I built SQL-based pipelines to consolidate, validate, and prepare large datasets from multiple sources.

I performed data cleaning, quality checks, and consistency validation to improve analytical reliability. I generated summary reports and dashboards supporting credit risk monitoring and decision-making.

I developed data-processing tools and automated workflows for operational and reporting systems. I created SQL and VBA scripts for data extraction, transformation, analysis, and routine automation across multiple environments.

I supported operational reporting by improving the efficiency and consistency of data-driven processes.

I produced quantitative reports for structured products and derivatives and supported sales and trading desks with pricing and statistical analysis. I developed VBA and SQL tools that improved the efficiency of internal routines.

I contributed to quantitative analysis workflows used for derivatives-related reporting, product support, and trading decisions.

Research focuses on machine learning methods for option pricing, portfolio decision-making, and risk management, including optimal stopping, volatility surfaces, probabilistic modeling, and deep learning architectures for derivatives.

Thesis: Pricing of American options using optimal stopping techniques and neural networks applied to the Brazilian market.