I'm a Data Science student at the University of Florida, graduating May 2027, and continuing into the M.S. Statistics program through 2029. I'm working toward a career in quantitative research — building the statistical depth, programming foundations, and financial intuition to do rigorous empirical work in that space.

My background sits at the intersection of statistical modeling, algorithm design, and applied data analysis. I'm comfortable in both Python and C++, and I care about doing things correctly — documented assumptions, honest reporting of results, and methodology that holds up under scrutiny.

An end-to-end factor research framework backtesting momentum, low volatility, earnings yield, and short-term reversal signals on S&P 500 constituents (2005–2024). Full lookahead bias prevention, transaction cost modeling, and rigorous documentation of why survivorship bias inverted two of the four hypotheses. The most important finding was methodological: data source selection matters more than factor model choice.

Python Pandas yfinance Quantitative Finance Backtesting

Quantitative research project applying time series methodology and permutation-based statistical testing to detect meta shifts in high-elo Teamfight Tactics gameplay. Collected 23,374 match records via the Riot Games API, engineered a trait-level time series, and identified 5 statistically significant shifts at the patch 10→11 boundary. Includes a stabilization analysis measuring variance compression within patch windows — methodology mirrors regime detection in quantitative finance.

Python Pandas SciPy Plotly Streamlit Time Series Permutation Testing

Geospatial trail visualization tool built with OSMnx and Folium. Pulls real hiking trail data from OpenStreetMap, computes optimal routes across trail networks using graph algorithms, and renders interactive maps with elevation and distance metadata. Motivated by a real trip planning problem.

Python OSMnx Folium Graph Algorithms Geospatial

Collaborative academic project. Led the modeling pipeline — evaluated linear, polynomial, and exponential decay models across 295 observations from 65 runners; selected the best functional form via residual analysis and held-out RMSE. The asymptotic parameter of the winning model estimates a runner's theoretical performance floor.

Python SciPy Pandas Matplotlib Predictive Modeling

C++ graph-based campus navigation system implementing BFS, Dijkstra's shortest-path, and Prim's MST on a 55-node, 72-edge weighted directed graph of UF campus buildings. Includes a student schedule manager with CSV-driven data loading and conflict validation.

C++ Graph Algorithms Dijkstra BFS Data Structures

My individual component for a collaborative CVE Finder project. A from-scratch Red-Black Tree implementation guaranteeing O(log n) insert and search, with CVE identifiers encoded as integer keys to preserve chronological ordering. Includes an invariant validator tested against adversarial insertion sequences.

C++ Data Structures Algorithms CMake

• 📚 Taking Mathematical Statistics II, Regression Analysis, Statistical Learning, and Bayesian Methods
• 📖 Working through A Primer for the Mathematics of Financial Engineering — Stefanica
• 🎯 Targeting quantitative research internships for Summer 2028

Languages: Python · C++ · R · SQL
Libraries: NumPy · Pandas · Scikit-learn · Matplotlib · SciPy · Plotly · Streamlit · yfinance · OSMnx · Folium
Tools: Git · Jupyter · CMake · VS Code

University of Florida · B.S. Data Science (May 2027) · M.S. Statistics (May 2029)