Worked on a team of data engineers, data analysts and data scientists focused on reporting, machine-learning, genAI, cloud and visualization. Built and managed a company-wide private LLM bot that automates tasks across applications, interacts with users using Retrieval-Augmented Generation (RAG) for document searching and accesses external knowledge using top-performing LLM models.Built and managed an end-to-end scalable machine-learning pipeline that streamlines model building, scoring and performance and is portable across client accounts on AWS. Built and managed a Python based module that simplifies and automates workflow in AWS. Interacted daily with core data science tools and AWS services (SQL, Python, SageMaker, Docker, Bedrock, Lambda, Glue, Step Functions, Athena, S3, Tableau, Git, Hive, Iceberg).Worked on client projects focused primarily on marketing and loyalty optimization. Collaborated across my team conducting code reviews, establishing best practices and exploring new functionality to expand and grow our products, expertise and skillsets.Phaedon was formerly ICF Next.

Assisted in leading the analytic strategy for Banking & Cash Solutions business, specifically: Certificates, Visa, Personal Trust Services, Mortgage and Securities Based Lending.Developed and managed several predictive models to understand client propensity to purchase and advisor propensity to sell Bank products.Built and managed marketing analytics dashboards for Bank products, providing insight on marketing campaign performance and contact optimization (i.e. model decile, opt-out and contact history tracking).Acted as a data and analytics expert for Bank to build, manage and execute analytic use-cases as they adopted a new cloud-based Amazon AWS environment for analytics and data storage.