Blaise Beavogui
Work Preference
Summary
Driven graduate research student with expertise in statistical analysis and risk modeling. Known for effectively collaborating on complex projects and delivering insightful data visualizations. Prepared to apply analytical skills to enhance organizational outcomes.
Overview
8
8
years of professional experience
Work History
Quantitative Research Analyst
LFT Algorightms
Eau Claire, Wisconsin
10.2025 - Current
- Constructed end-to-end intraday research pipeline for COMEX Gold calendar spreads across 12 delivery months.
- Engineered robust features, including rolling median and z-score, ensuring leak-free performance.
- Designed mean-reversion baseline with transaction-cost floors and realistic slippage enforcement.
- Implemented walk-forward in-sample/out-of-sample testing with parameter optimization over specified ranges.
- Generated out-of-sample leaderboard and frozen parameters for 12 adjacent pairs, showcasing key highlights.
- Utilized Python libraries like pandas and NumPy for data management and analysis.
- Developed CI-style reproducible notebook workflow to ensure data quality and schema enforcement.
- Collaborated with cross-functional teams to enhance research methodologies and frameworks.
- Developed predictive models to support investment strategies and risk assessment.
- Utilized software tools for data manipulation, analysis, and reporting tasks efficiently.
- Developed and implemented statistical models to analyze customer behavior.
- Performed regression analysis to determine correlations between variables.
- Maintained an up-to-date knowledge base on emerging trends in the field of quantitative research.
Graduate Research Student
University of Minnesota, Twin Cities Campus
Minneapolis, Minnesota
01.2024 - 07.2025
- Constructed Generalized Linear Models for stress-testing large mortgage-backed datasets, estimating default probability across diverse scenarios.
- Analyzed data using statistical software to derive meaningful insights.
- Collaborated with faculty and peers on interdisciplinary research initiatives.
- Assisted in mentoring undergraduate students in research methodologies.
- Developed proposals for grant funding to support research activities.
- Cleaned and validated high-volume datasets using Python and Excel to ensure model reliability.
- Executed scenario analysis to pinpoint key risk drivers, including DTI and interest-rate environments.
- Generated comprehensive analytics reports summarizing risk insights and model performance.
- Cooperated with practitioners to align models with industry-standard risk practices.
- Enhanced documentation, validation, and communication of model results.
Risk Modeling & Stress Testing Workshop
University of Minnesota – Minnesota Center for Fin
Minneapolis, Minnesota
01.2025 - 04.2025
- Analyzed extensive Fannie Mae loan datasets to develop stress testing models for mortgage default risk.
- Worked successfully with diverse group of coworkers to accomplish goals and address issues related to our products and services.
- Promoted high customer satisfaction by resolving problems with knowledgeable and friendly service.
- Assisted with customer requests and answered questions to improve satisfaction.
- Built Excel dashboards utilizing pivot tables, VLOOKUPs, and data visualizations for presenting risk scenarios.
- Applied statistical concepts in Python and Excel to evaluate risk exposure effectively.
- Delivered comprehensive report summarizing risk insights and model outcomes, adhering to industry standards.
- Strengthened technical documentation and data wrangling skills to clarify complex problem statements.
- Employed Generalized Linear Models (GLM) and stress-testing techniques to quantify credit and market risk exposures.
Graduate Student Teaching Assistant
University of Minnesota
Duluth, Minnesota
08.2017 - 05.2019
- Graded assignments and provided constructive feedback to students.
- Assisted professors in preparing course materials and lectures.
- Facilitated discussions and group activities to enhance student engagement.
- Supported students during office hours, addressing questions and concerns.
- Collaborated with faculty on curriculum development and assessment strategies.
- Collaborated with faculty members on special projects related to teaching and learning initiatives.
- Created and managed a positive classroom environment conducive to learning.
Education
Master of Science - Finance
University of Minnesota
12-2026
Master of Science - Applied Statistics
University of Minnesota
05-2019
Bachelor of Science - Applied Mathematics
University of Minnesota
05-2016
Skills
- Statistical analysis and modeling
- Data visualization and interpretation
- SQL and database management
- C# and Python programming
- Project management and collaboration
- Risk assessment and mitigation
- Data cleaning and validation
- Machine learning and predictive analytics
- Business intelligence and data governance
- Excel functions and pivot tables
- Data mining and extraction techniques
- Educational technology integration
- Software development practices
- API documentation and RESTful services
Monte Carlo Exotic Options Pricing Web API Project
Built a web API using ASP.NET Core for pricing exotic financial derivatives (e.g., Asian, Lookback, and Digital options) via Monte Carlo simulation.
- Designed API endpoints to receive pricing parameters and return option prices, Greeks, and standard error.
- Integrated support for antithetic variates and simulation controls.
- Developed both backend logic (C#) and simple frontend (HTML/JS using fetch) for testing.
- Applied RESTful design and used Thunder Client/Postman for testing.
- Optionally: Used Entity Framework for database interactions and project structure with multiple class libraries.
Tech Stack:
C#, ASP.NET Core, Web API, HTML/JavaScript (frontend), Entity Framework (optional), Thunder Client/Postman (testing)
MLFactor Equity Strategy — Research Project (2024–2025)
- Built a full machine-learning equity selection system using 20 years of global equity data (2000–2018).
- Engineered financial features and applied hierarchical clustering to reduce 93 raw factors to a compact set of 30–35 orthogonal predictive signals.
- Implemented and compared Ridge Regression, Neural Network Regression, and Neural Network Classification across 65 hyperparameter configurations.
- Developed multiple portfolio-construction methods (regression weighting, long/short quintile strategy, hybrid direction-magnitude model).
- Designed a monthly-rebalanced trading strategy using ML-generated forecasts; tested rolling lookback windows (36M/60M/84M/expanding).
- Achieved best performance with Ridge Regression (60-month lookback):
Sharpe: 1.04, Max Drawdown: –3.9%, significantly outperforming equal-weighted benchmark Sharpe (0.58). - Implemented full backtesting engine (turnover, performance metrics, benchmark comparison).
- Tools: Python, sklearn, pandas, numpy, TensorFlow/Keras, Matplotlib, Quarto.
Languages
English
Full Professional
French
Native or Bilingual
Name
Hi, I’m
Education and Training
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Accomplishments
Technologies Used Features
Monte Carlo Option Pricer is a full-stack web application that prices financial derivatives using Monte Carlo simulation. Built with ASP.NET Core on the backend and HTML/CSS/JavaScript on the frontend, the tool allows users to configure option parameters and view the resulting price along with its sensitivity metrics (the Greeks).
The application supports European and barrier options, with optional variance reduction techniques like antithetic variates and control variates. Users can input custom values for spot price, strike, volatility, interest rate, time to maturity, and more.
Simulations run entirely on the server side for performance and accuracy, while the frontend delivers a clean, responsive interface for input and results visualization. The app is deployed via Docker on Render, making it accessible from any browser.
- ASP.NET Core 8 (C#)
- HTML, CSS, JavaScript (Vanilla)
- Docker
- Render (Cloud Deployment)
- Monte Carlo pricing of European and barrier options
- Calculation of Greeks: Delta, Gamma, Vega, Theta, Rho
- User-selectable simulation parameters (steps, number of paths)
- Optional variance reduction (antithetic & control variates)
- Responsive frontend with real-time result display
Interests
Financial Markets, Mathematics, Coding, Reading
Work Availability
monday
tuesday
wednesday
thursday
friday
saturday
sunday
morning
afternoon
evening
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Affiliations
- Society for Industrial and Applied Mathematics
Software
C#
Python
Javascript
Quote
Judge a man by his questions rather than his answers.
Voltaire
Timeline
Quantitative Research Analyst
LFT Algorightms
10.2025 - Current
Risk Modeling & Stress Testing Workshop
University of Minnesota – Minnesota Center for Fin
01.2025 - 04.2025
Graduate Research Student
University of Minnesota, Twin Cities Campus
01.2024 - 07.2025
Graduate Student Teaching Assistant
University of Minnesota
08.2017 - 05.2019
Master of Science - Finance
University of Minnesota
Master of Science - Applied Statistics
University of Minnesota
Bachelor of Science - Applied Mathematics
University of Minnesota