🎯 Actuarial Science | Predictive Analytics | Mathematical Modeling | Machine Learning
Actuarial professional with over a decade of experience across consulting and industry roles.
I hold a B.S. in Actuarial Science, Mathematics, and Statistics from the University of Iowa and focus on applying quantitative methods to real-world problems in insurance, finance, and sports analytics.
- 🔭 Building projects in actuarial modeling, predictive analytics, and machine learning
- 🌱 Deepening expertise in statistical learning theory and applied ML
- 👯 Open to open-source collaboration and applied research
- 🤝 Interested in strengthening computer science fundamentals for scalable analytics
- 💬 Ask me about:
- Actuarial modeling & reserving
- Predictive analytics
- Statistical & machine learning methods
- Programming in C++, C#, Python, R, Julia, and SQL
- ⚡ Fun fact: I enjoy sports, music, and food
📫 Contact: [email protected]
👨💻 Projects & portfolio: https://jeffmaxey.github.io/
- Actuarial modeling
- Statistical inference
- Predictive analytics
- Machine learning & optimization
- Time series & simulation
- Python, R, Julia
- C++, C#
- SQL
- NumPy, pandas, scikit-learn
- PyTorch, TensorFlow, Keras
- MLflow, Hugging Face, LangChain
- Jupyter, Streamlit, Gradio
- Docker, Kubernetes
- Git, CI/CD (GitHub Actions, CircleCI, Travis CI)
- FastAPI, Flask, Django
- Linux, Bash
- AWS, Azure
- PostgreSQL, MySQL, SQL Server
- MongoDB, Redis
- D3.js, Chart.js
- React, Vue
- HTML, CSS, TypeScript
🧭 Emphasis is on robust modeling and analytics, with engineering tools used to support production-quality workflows.
I focus on projects that connect theory → implementation → impact, including:
- Actuarial & insurance modeling
- Predictive analytics for finance and sports
- Statistical and machine learning research
- Open-source tooling for quantitative workflows
➡️ See pinned repositories and my website for highlights.
