I am interested in structural uncertainty — how complex systems behave under stress, how vulnerabilities emerge, and how hidden dependencies shape outcomes. My work focuses on modeling risk rigorously and translating detection into strategic decision-making.

I am particularly drawn to:

• Behavioral anomaly detection
• Financial risk diagnostics
• System fragility and regime shifts
• Attack surface and vulnerability modeling
• Risk-adjusted decision frameworks

I am motivated by understanding not just what happens in a system, but why it breaks — and what should be done about it.

Risk Modeling · Anomaly Detection · Financial Diagnostics · ETL Pipelines ·
Predictive Modeling · Cloud Analytics · Business Intelligence · Process Optimization ·
Financial Valuation · Innovation & Technology Strategy

Google Cybersecurity Certificate
Supervised Learning with scikit-learn
Intermediate Regression with statsmodels
Hypothesis Testing in Python
Joining Data in SQL
Excel Skills for Business (Goldman Sachs)
Asset Allocation in Investment
GE Aerospace Digital Technology
J.P. Morgan Investment Banking
Oliver Wyman – Financial Services: Climate Change

Designing resilient systems where detection, modeling, and decision-making converge in high-stakes environments.

Security is not only technical — it is structural. I am fascinated by how systems fail, how incentives distort behavior, and how data reveals hidden patterns. My long-term goal is to build advisory frameworks that strengthen cyber resilience in high-stakes environments.