- Evaluated and groomed AI/ML use cases using the AI Intake and Prioritization framework, resulting in the identification and development of 6 high-impact projects that aligned with business goals.
- Validated and enhanced AI models, improving model performance by 22% and supporting the integration of advanced data science solutions in finance projects, contributing to enterprise-level ML/NLP initiatives.
- Optimized AI technology adoption by assessing over 5 vendor solutions, ensuring the alignment of new tools with advanced data analytics and financial modeling needs.