• Successfully completed a strategic exit by selling my equity stake in the asset management firm after leading the development of its quantitative technology.• Led the development of Kairos, a cloud-based autonomous algorithmic asset management platform, which successfully reduced portfolio volatility from 15% to 2% and mitigated drawdown for Polyface Invest. Grounded in Nassim Taleb's , Kairos introduced the first neutral tail hedge product, designed to protect portfolios from global conflicts while achieving up to 300% appreciation during market crash, ensuring gains without depreciation in extreme volatile conditions.• Conduct independent validation of market risk models, ensuring alignment with regulatory requirements and internal benchmarks, while automating testing procedures to enhance efficiency and accuracy.• Applied advanced models, factor analysis, and deep learning algorithms (NARX, Liquid State Machine, Hidden Markov Models) across USD, fixed income, and equities to optimize trading and mitigate risks.• HRP, Kelly Criterion, VaR, CVaR, EVaR and extreme event stress testing with MCMC fat tails distributions, along with a proprietary internal technology that analyzed 20 different statistical measures and ran automated risk tests and algorithmic portfolio rebalancing to ensure portfolio resilience and tail hedge risk-adjusted returns.• Develop and maintain model risk baselines, tracking model performance over time to ensure consistency, reliability, and alignment with evolving market conditions and business objectives.

• Designed asset's quantitative area from scratch to operation, including strategic plans, sub-areas, and research processes.• Collaborate with cross-functional teams to translate complex data into actionable insights for product innovation and strategic business decisions.• Advise stakeholders on risk mitigation strategies, utilizing data-driven approaches and predictive analytics to inform risk models and shape product roadmaps that address the investment hedge thesis..• Design and deploy sophisticated quantitative models that optimize portfolio risk, leveraging advanced data science techniques and ensuring seamless integration into risk mitigation product development workflows.• Python, mathematical, statistical, deep learning, and computational techniques for practical solutions in asset allocation risk management, top-down and bottom-up analysis, and pricing options.

Aureaum is the rebranding of Krhatos, evolving to meet growing demands for AI and data science in risk management and financial analytics.• Executed a strategic exit, highlighting business growth and delivering value to stakeholders.• Developed AI/ML-driven data products for optimizing industrial efficiency, including predictive maintenance, workforce scheduling automation, and supply chain demand forecasting. Additionally, applied advanced models for sports data analysis, anticipating consumer trends, scaling automation, optimizing long-only portfolios, and analyzing scenario simulations in production chains, significantly enhancing decision-making and operational performance across various sectors.• Implemented advanced analytics for product optimization and fraud detection, driving profitability and safeguarding businesses from financial risks.• Conceptualized and developed Shiva AI, a pioneering solution for continuous organizational evaluation and risk monitoring, addressing key operational vulnerabilities.• Provided strategic advisory services to clients, solving complex business challenges through the application of machine learning, advanced analytics, and big data, ensuring actionable and scalable results.• Collaborated with stakeholders across departments to define data product goals, prioritize features, and ensure alignment with overall business strategy and market needs, delivering impactful data solutions.

Khratos is an AI startup leveraging machine learning and proprietary algorithms to transform data into strategic insights, enabling organizations to make informed decisions in uncertain environments.• Builds custom AI algorithms and models, applying machine learning techniques such as fraud detection, volatility analysis, and churn reduction to deliver tailored business solutions that enhance operational efficiency and mitigate risk.• Conducted market research and user testing to validate product concepts, ensuring features meet customer expectations and drive adoption while maintaining competitive differentiation in the marketplace.• Utilizes predictive modeling and scikit-learn's ensemble methods (such as random forests and boosting techniques) to optimize business processes, ensuring scalability and resilience in decision-making frameworks.• Selected for TOTVS' open innovation program (iDexo), showcasing its cutting-edge capabilities in data-driven decision-making.• Developed and maintained the product roadmap, aligning long-term business objectives with short-term deliverables, ensuring all stakeholders were informed and on board with product timelines and milestones.

• Provided technical support for communication infrastructure, including server network monitoring and internal systems management at headquarters, ensuring compliance with Army Command's information security protocols.• Participated in key military operations, such as Operation Black Needles, and completed an airmobile combatant internship.

• Performing vulnerability monitoring in technological environments with more than 10,000 terminals and 1,000 servers for national and international clients (financial banks, airlines, television stations, among other market leadership companies).• Research and application of security baselines in Microsoft environments and in several databases ( SQL Server , Oracle , MySQL, PostgreSQL ).