Daniel Wooten

Programming Languages: Python 3 (10+ years), C/C++/C# (5+ years), Java (2+ years)

Tools: Pandas, Numpy, RegEx, Scikit-learn, Matplotlib, PyTorch, CUDA

Communication: Expert public speaker and technical communicator; skilled at bridging the gap between complex research and stakeholder needs.

Principal Data Scientist: Gen-AI - Capital One Bank - Dec 2024 to Present
- Designed and deployed LLM model for credit risk evaluation increasing accuracy by 4.5% resulting in NPV over $90 million
- Created and launched LLM-Judge for LLM output evaluation resulting in $300k annual savings
- Patent-pending on novel LLM analysis technique for boosting GBMs with first results worth $7.5 million annually

Principal Data Scientist: Anti-Money Laundering - Capital One Bank - Jan 2023 to Dec 2024
- Designed and deployed LLM model for risk-leveling increasing AUROC by 14% worth more than $1.2 million annually
- Reduced alert volumes by more than 15% through model optimization, reducing investigations cost by $800k annually
- Developed and deployed new model features increasing risk coverage by 11%

AI/ML Software Engineer - Perceptronics Solutions - Aug 2020 to Jan 2023
- Designed and built Auto-Encoder model for AI-generated-radar detection and classification resulting in 3-year contract renewal
- Created a Bayesian filter based planning tool for coordinating multiple independent actors resulting in 3-year contract renewal

UC Berkeley - Dec '19
Ph.D. in Nuclear Engineering: Designated Emphasis in Computational and Data Science Engineering