Led end-to-end project development from ideation to deployment, automating analytical scripts and enhancing reporting mechanisms, resulting in significant time savings and increased operational efficiency. Designed and maintained scalable data pipelines utilizing R, Python, SQL, and PySpark (Databricks) to support large-scale data analysis, including implementing a barcode API integration in Power BI to streamline UPC scanning functionality on Android devices. Developed and integrated critical reports in Power BI, consolidating redundant reporting structures to create streamlined and comprehensive performance dashboards. Orchestrated the migration of legacy on-premises data workflows to cloud-native architectures using Databricks, optimizing the delivery pipeline for key performance metrics and significantly enhancing user accessibility and scalability. Collaborated with cross-functional teams to align data solutions with business objectives, thereby facilitating informed, data-driven decision-making processes.

Specialized in empowering small-scale early stage startups by delivering highly accurate machine learning models optimized for small datasets.Enabled startups to harness AI without the need for extensive data resources.Challenged industry norms by supporting the argument that small data holds enough insights to build effective ML models and analytics.Accelerated client growth by enhancing decision-making processes through tailored solutions.

• Partner with AFT/RME/OPS/AR teams to help automate and improve KCVG's Amazon Robotics floor through an iterative process. (Amazon's newest and biggest $1.5B air hub)• Directly responsible for the success of the AR department during sortation. Oversee 1.6 million square feet of equipment, Amazon's first dual main distribution frame (MDF) AR floor, 1950 AR drive units, 23 Artemis manual induct stations and 48 Robin induct work cells.• Pioneer state-of-the-art technologies and internal propriety software found in an Amazon sort facility.• Develop and promote talent within teams using data-centric projects.• Utilize the 5 elements of Kaizen to continuously improve the AR department such as forward-thinking projects that automate lengthy processes.

• Updated SQL rules and automation • Improved system performance• Designed agent deployment topology• Designed user-accessible software deployments • Implemented unused features • Helped redesign major aspects of current helpdesk system

• Researched, extracted, cleaned, and managed data on potential consumer leads• Analyzed complex data sets using basic analytical tools and models • Prepared findings in a professional manner