VaR, stress testing, and loss forecasting
Built and validated Monte Carlo VaR and probabilistic loss models with scenario analysis, sensitivity testing, statistical validation, and documentation controls.
New York, NY • Quantitative Risk & Analytics
Building risk models data systems and decision tools for capital portfolio and strategy teams.
Quantitative analytics professional with 5+ years of experience building Python and SQL based models for VaR, stress testing, probabilistic loss forecasting, scenario analysis, sensitivity analysis, and senior-stakeholder decision support.
CFA Level II Passed
MBA
Python / SQL
Risk Modeling
Market Risk
VaR
Stress Testing
Data Engineering
Capital Analytics
Fixed Income
Impact Summary
Analytics that connect quantitative rigor to operational decisions.
I specialize in turning ambiguous risk, economic, and financial questions into structured datasets, defensible models, and clear executive recommendations.
Large-scale analytical datasets
Engineered Python and SQL workflows across 200,000+ observations to support modeling, reporting, and reproducible analysis.
Senior-stakeholder communication
Translated technical model outputs into risk drivers, funding tradeoffs, capital-impact narratives, and clear decision materials for leadership.
Resume
Professional Experience
Current federal economist with a quantitative risk, financial analytics, and technical software-development profile.
June 2020 — Present
Economist
United States Army Corps of Engineers — New York District
- Develop Python and SQL based quantitative models for risk, forecasting, probabilistic loss analysis, economic benefits, and scenario based decision support.
- Built and validated Monte Carlo VaR and probabilistic loss models, including sensitivity analysis, scenario analysis, and model documentation controls.
- Engineered large scale datasets across 200,000+ observations using Python, SQLite, SQL Server, and geospatial workflows in ArcGIS Pro.
- Analyzed international trade, shipping vessel data, market conditions, and cost risk scenarios to assess project impacts on East Coast ports.
- Wrote C# unit and integration tests for HEC-FDA flood damage risk modeling software to improve software quality and analytical reliability.
- Prepared reports and presentations translating technical analysis into recommendations for senior staff and external stakeholders.
Education & Credentials
MBA + Quantitative Finance Training
- MBA, University of Ljubljana, Faculty of Economics
- B.S. Business Administration, University of North Carolina Wilmington
- CFA Level II Passed; CFA Level I Passed
- CompTIA Security+ certification
Portfolio Direction
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ASP.NET • Enterprise
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Enterprise-style risk tracking application with authentication, PostgreSQL, Docker deployment, exports, and structured note workflows.
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Django • Data Platform
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Personal research site concept for dashboards, market data APIs, research notes, portfolio analytics, and deployed Python services.
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Technical Toolkit
Risk analytics plus production software fundamentals.
Programming & Analytics
Python, SQL, R, C#, Go, JavaScript, pandas, NumPy, SciPy, scikit-learn
Risk & Statistical Modeling
VaR, Monte Carlo simulation, probabilistic loss modeling, tail risk analysis, stress testing, sensitivity analysis, backtesting, model validation
Databases & Infrastructure
PostgreSQL, SQL Server, SQLite, DuckDB, Docker, Git, Linux, ETL development, large scale dataset engineering
Finance & Decision Support
Fixed income fundamentals, interest rate sensitivity, yield curve dynamics, credit spread analysis, economic modeling, capital allocation
Contact
Open to quantitative risk, analytics, and financial technology opportunities.
Based in the New York City area. Available for roles involving market risk, fixed income analytics, capital strategy, risk data engineering, and Python/SQL based analytical software.
