Edward Eddie Jenkins

Machine Learning Development and Implementation:
- Utilized pre-trained transformer models to gather semantic contextual embeddings for customer and product master attributes and perform segmentation across four clients in different industries
- Created an XGBoost model in R that generated win/loss probabilities and optimized client margin target recommendations based on the expected value of the quote
- Built and implemented XGBoost in Python to produce monthly target margin recommendations for thousands of customer/product combinations based on client historical transaction data
- Employed mixed effects regression modeling to align historical costs and margins to account for market and business strategy changes to utilize in pricing model development

Production API Model Development:
- Defined requirements across all involved teams and built the model implementation of a framework that allowed clients to test and deploy new model parameters within their application
- Developed and released production ML models within the CI/CD framework in Github
- Leveraged PyTest unit testing infrastructure to ensure long-term stability of deployed code

Model Communication:
- Created and presented content to C-Suite level audiences to communicate pricing model structure
- Recommended and explained advanced statistical and machine learning approaches to non-technical project delivery teams

Internal Team Development:
- Led Associate Data Scientists through implementations of technical projects and provided guidance on next steps for machine learning and statistical analyses
- Conducted over 50 interviews for Data Scientist candidates including live coding and case study