● AI Solution Design: Tailored AI strategies that fit seamlessly into your business model, powered by Google Cloud's Vertex AI. We design, develop, and deploy scalable AI solutions that not only solve challenges but also create value.● AI Consulting: Expert guidance at every step of your AI journey. From initial assessment to full-scale implementation, our consultants are here to ensure your AI initiatives succeed with maximum impact and minimal risk.● Professional Training: Elevate your team's AI expertise. Our comprehensive training programs are crafted to enhance your understanding and skills in artificial intelligence, preparing you for the demands of future technology.● US Department of Energy (Client): Lead data scientist for Strategic Petroleum Reserve Gulf Coast Hurricane Prediction Model● Levi Strauss & Co. (Client): Led development of the Demand Planning team’s Computer Vision and Natural Language Processing (NLP) product similarity-matching model resulting in reduced customer shipping time and improved in-store product availability● Cisco Systems (Client): Training and curriculum designer for several live, in-person training classes including: "ML Fundamentals with Python," "Deep Learning Fundamentals with Python," "Developing a Data Strategy," etc.● Anaconda (Client): Training and curriculum designer for online training classes including "Developing an ML Pipeline End-to-End" and "Prompt Engineering Essentials"● Ipsos (Client): MLOps lead for Reputation Intelligence for Strategic Evaluation (RISE) Platform● Springboard (Client): Mentored, guided, and knowledge resource for five mentees during their completion of Springboard's online career tracks in data analytics, data science, and data engineering

● Lead machine learning engineer for Demand Planning team, Computer Vision, Natural Language Processing (NLP). ● Developed process standardization and documentation best practices across data science, ML engineering, and MLOps teams resulting in improved team collaboration.● Managed release process resulting in a systematized approach to enterprise machine learning model deployment.● Collaborated with Director of Machine Learning Production and Support Operations for developing and socializing the team charter resulting in greater team cohesion between data engineering, data science, ML engineering, and MLOps● Lead developer for machine learning project support onboarding including knowledge transfer, documentation standards, and hyper care for the Data and Artificial Intelligence Team● Machine Learning Quality Assurance team lead for the development and implementation of model performance metric monitoring across e-commerce recommendation engines● Machine Learning Quality Assurance team lead for developing best practices and gold standards across the Data and Artificial Intelligence Team resulting in reduced time to production, proactive incident management, and improved coding standards● Lead role in the two-year cloud migration between Amazon Web Services (AWS) and Google Cloud Platform (GCP)

● Provided advice and guidance for Cohort 12 regarding data strategy and machine learning

● Product Manager of $14M Syndicated Research and Primary Research custom studies in energy/utility, consumer technology, consumer finance, P&C insurance, and health insurance industries