Data Scientist | Master's in Analytics from Georgia Tech
I am a data scientist with a Master of Science in Analytics from Georgia Tech, specializing in predictive modeling, statistical inference, and decision-focused analytics. My work centers on transforming complex, messy datasets into structured models that support clear, defensible decisions.
I bring a hybrid background in analytics and finance, which allows me to think beyond model accuracy and focus on economic impact, risk, and real-world constraints. I have built probabilistic models, regression frameworks, and machine learning systems across sports analytics, valuation modeling, and performance optimization contexts. My experience includes hierarchical modeling, feature engineering for large event-level datasets, model validation, and translating technical outputs into actionable recommendations.
Technically, I work primarily in Python (pandas, scikit-learn, statsmodels, PyMC), SQL, and statistical modeling environments. I am comfortable designing full workflows: data cleaning, feature construction, model development, evaluation, and clear presentation of results.
I am particularly well-suited for projects involving:
- Predictive modeling and forecasting
- Decision support systems
- Bayesian or probabilistic modeling
- Feature engineering and structured dataset design
- Model evaluation and validation frameworks
- Translating complex analysis into clear business insight