PhD Quant & AI Expert | 15+ Years Bridging Stochastic Rigor and Institutional Scale
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About Me
The Bridge Between Doctoral Rigor and Industrial Execution.
I am a PhD in Applied Mathematics and Mathematical Engineer with 15+ years of experience leading quantitative risk frameworks for systemic financial institutions managing $100Bn+ in assets.
My career is defined by a unique duality: I hold the institutional discipline of the 2nd Line of Defense (achieving "Zero Technical Findings" in regulatory audits) while maintaining a deep mathematical focus on Energy and Commodities volatility.
What I bring to the table:
Institutional Scale: Lead roles at MUFG, BTG Pactual, and Bci, architecting IRRBB, IFRS 9, and Basel III frameworks.
Energy & Commodity Depth: Valuation of large-scale infrastructure for Petrobras and current R&D on Bitcoin Mining energy-arbitrage models.
AI & Tech Innovation: Founder of Quant-AI-Lab, where I deploy Physics-Informed Neural Networks (PINNs) and RAG systems in production-grade Cloud environments (PySpark/Azure).
Expert Authority: Court-Appointed Judicial Expert for AI and Finance litigation.
The "Fast-Track" Advantage (For US/Canada Recruiters):
I am a Chilean citizen, which provides a massive logistical and fiscal edge:
USA: Eligible for the H-1B1 Treaty Visa (No lottery, available year-round, and strictly exempt from the new $100,000 surcharge).
Canada: Eligible for the Global Talent Stream (Expedited 2-week processing).
Looking for: Senior/Executive opportunities in Quantitative Risk, Model Validation, or Quant Research where deep stochastic modeling meets high-stakes decision-making.
Let’s connect if you need a specialist who can navigate complex energy derivatives and high-level banking governance with equal precision.More...
Felipe Fritsch
Graduate Student, Mathematics@University of Oxford
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Graduate Student in the Mathematical Institute at the University of Oxford, specializing in mathematical and computational finance.
Particularly passionate about the intersection of deep learning and its applications to macrofinance / asset pricing and market efficiency via a trading perspective.
Originally from Rio de Janeiro (Brazil), I graduated with honors from Columbia University in 2020 as a double major (B.A.) in Applied Mathematics and Economics — during which I was a TA in the Mathematics department for 3 semesters.
Worked for 2+ years at AQR as a quant researcher in systematic credit, then moved back to Brazil and focused in deep learning and GenAI for 1-2 years prior to joining Oxford — notably, led the development of an in-house multi-agentic RAG application at one of the country’s largest hedge funds.
Proficient primarily in Python (particularly ML research, API backend development, and building agentic workflows using LLM’s own libraries / leveraging LangChain and Pydantic). Also competent in R, SQL, C++, Git, JavaScript, and HTML.
Also love football, rowing, sports betting & trading, and teaching more “fundamental” mathematica/statistics/economics/finance topics (up to undergraduate level, or beyond if within my research scope).More...
Glaucio Silva
Solution and Software Architect
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With over 20 years of experience in backend development and solution architecture, I help companies scale their operations with security, availability and cost optimization. I am the founder of Carvanny Software Engineering, where I work on creating efficient solutions for cloud environments, systems integration and information security.
💡 My specialties:
✔ AWS Solution Architecture
✔ Backend development in Java, NodeJS and Python
✔ APIs, Microservices and System Integration
✔ Strategies for cost optimization and high availability
✔ Information Security and compliance in cloud environmentsMore...