• Creating new and improving existing machine learning algorithms, such as random forest and gradient boosted decision trees models, for bid adjustment to optimize programmatic advertising campaigns

• Designed and tested live statistical testing algorithm to evaluate and monitor AI-controlled programmatic advertising campaigns

• Built performance uplift evaluator to assess the performance of previous advertising campaigns using our AI campaign management software

• Implemented in production feature engineering techniques to reduce computational requirements by over 90% in our bid adjustment algorithm data pipelines

• Provided data-driven solutions in the forms of classifier, clustering, and physical models in Python for inventory management and process development, resulting in millions of USD generated revenue

• Interfaced with business, technology, customers, and external collaborators to support materials manufacturing

• Engage in cross-functional teams to support scale-up processes for materials including zeolites, metal oxides, and support metal extrudate catalysts

• Leader of lab-scale evaluations, process challenges, and troubleshooting to inform technology transfers to manufacturing of catalysis synthesis processes

• Developed a physical chemical and economical model in MATLAB to successfully evaluate process technologies, which resulted in over $1 million in research resources saved

• Invented and patented (two patent applications and one peer-reviewed publication) novel catalyst material and process technologies

• Provided technical solutions to dry etch process manufacturing for the development of novel semiconductor technologies