I'm building and scaling the Customer Engineering and Customer Success Organization at Comet.• Establishing and mentoring a team of Technical Account Managers, Support Engineers, and AI Architects to provide technical solutions and support to enterprise customer accounts.• Enhance customer success Playbooks and creating process to scale the CX operations internally • Leading the CS team to meet ARR goals and ensure renewals • Collaborating with customers to integrate Comet into their critical AI and ML Platforms and workflows, ensuring seamless implementation and measurable value form AI/ML initiatives • Creating and leading LLMOps and MLOps workshops and customer enablement sessions to enhance understanding and adoption of best practices for experiment and production phases of the AI/ML lifecycle

Advising local startups on AI strategy - Materian AI- FinGoal

• Hired and led a team of AI Solutions Engineers to support customers post sales.• Took ownership of renewals and expansions• Served as an architecture advisor for LLMs in production.• Partnered with AI execs and leaders to design, implement, and optimize MLOps ecosystems.

Led the MLOps Platform team for AI model pricing algorithms. Focused on deployment, feature store, and decision engines.

As engineering manager, I established a scrum team of 7 full-stack Machine Learning Engineers. Our team created infrastructure for training, deploying, and maintaining our ML Models at scale. We executed the data engineering, model training, and software engineering phases of the project to deliver a Feature Store and Inference APIs that integrate into our customer facing products.

As tech lead I worked with PMs to scope ML project opportunities, led ML model training projects, and designed our MLOps systems

Trunk Club is a Chicago-based personalized styling service for men and women, offering both virtual and in-person shopping options.My work as a Data Scientist included:* Contributions to product recommendations and the style swipes project. • Research, develop, and implement predictive algorithms using various machine learning techniques, deploying them as real-time APIs in a micro-service infrastructure.• Utilize Natural Language Processing to understand text content across products, including reviews and interactions between users, stylists, and products.• Use Computer Vision or image content analysis of novel and existing clothing items: classification, quality, attractiveness, similarity, extraction of features for ranking models.• Use a range of clustering techniques to identify latent clusters of customers based on purchases, demographics, styles, etc.• Make personalized product recommendations using recommender systems such as collaborative and content based filtering and association rules.

Mosaic Data Science is a dynamic and growing Data Science consultancy solving some of the most complex and interesting Machine Learning problems in industry. As a Data Scientist at Mosaic, I have consulted for ExxonMobil, J. Crew, Schneider, and Anheuser Busch, where I applied machine learning and time series analysis in R and Python.

I provided statistical support to the Pueblo Chemical Agent-Destruction Plant: a chemical weapons demilitarization site in Pueblo, Colorado. My work included Laboratory predictive modeling, anomaly detection, data mining, time series forecasting, and experimental design.

Pacific Northwest National Laboratory. Operations Research Team.My position included statistical and mathematical research.

Reoccurring summer internships in the Statistical Sciences group at LANL. Researched Nuclear Materials Accounting methods under direction of Dr. Tom Burr. (See publications.)