Market intelligence in parallel with breakthrough Quantum Computing techniques, building competitive tools for trading, risk management, and large-scale optimization.
With a background spanning financial risk modeling and data engineering, the work sits at a rare intersection: understanding risk frameworks deeply enough to challenge them, and building the tools that provide stakeholders with line of sight to what matters most.
In addition to my core qork, I study computational approaches to modeling complex systems, including high-performance computing, network optimization, machine learning architectures, and methods of quantum computing. As demands and capabilities for statistical analysis advance in the economic ecosystem, the need for powerful hardware and software does as well. Quantum computing brings unprecedented processing power for simulating complex market scenarios, zero-day vulnerabilities, and 24x7 settlement, trading, and clearing.
In line with these advancements, my current research spans GPU-acceleration, stochastic techniques, neural network architectures, and variational quantum algorithms (VQE, QAOA) for large-scale simulation and optimization.
Equally at home writing a stress-test methodology as spinning up a reporting dashboard or an automated workflow. The goal is always the same: reduce uncertainty, surface insight, and equip decision-makers.
2LD ORM framework design, independent challenge, root cause analysis, and risk appetite alignment across complex regulatory environments.
KRI dashboards, trend analyses, and executive reporting using world-class software — turning raw risk data into actionable narratives.
Scalable workflow automation within Azure & AWS architecture built to embed governance into daily operations.
Formal internal control design, stress-testing, and gap analysis aligned with SEC, FINRA, CFTC, MiFID, and Basel III requirements.
ETL pipeline risk forecasting, network load modeling, and data trend analysis to anticipate and communicate emerging risk exposure.
Undergraduate grounding in both finance and computer science — enabling fluent communication across trading desks, tech teams, and regulators.
Architected an end-to-end KRI and ERM reporting suite connecting live data pipelines to executive dashboards. Reduced manual reporting cycles by 60% and surfaced previously invisible cross-regional risk concentrations.
Designed and stress-tested a formal internal control suite spanning operational, financial, and information security domains. Integrated automated evidence collection into M365 environment.
Built an automated data pipeline and submission framework for CFTC Reportable Event Reporting, reducing preparation time and ensuring consistent regulatory alignment across jurisdictions.
Leveraged regulatory and industry publications to build a network load forecasting model for ETL pipelines, enabling proactive risk identification ahead of peak processing windows.
Open to senior risk, quant, and adjacent roles — particularly where financial transactions meet data engineering. Always happy to connect with practitioners, researchers, and curious people.