I build practical systems that help teams make better decisions and move faster. My background spans forecasting, predictive modeling, reporting automation, workflow design, and AI-supported operational tools across retail, financial services, and collision-repair operations.
Clean, reshape, reconcile, and summarize messy real-world data so it becomes usable for decisions and operations.
Build recurring reporting workflows that reduce manual effort, improve reliability, and give teams timely visibility.
Replace repetitive manual steps with scripts, pipelines, and lightweight systems that save time and reduce errors.
Use practical programming to extract data, transform it, analyze it, and connect it to real business processes.
Develop forecasting processes and models that support planning, performance tracking, and operational decision-making.
Apply statistical and analytical modeling where it improves targeting, risk evaluation, or business outcomes.
Turn analysis into tools, outputs, and workflows that executives, operators, or managers can actually use.
Evaluate and implement AI-supported workflows where they add real operational value rather than just novelty.
A few examples of the kinds of problems Clewis has solved and the systems he has built.
Ecommerce analytics & forecasting
Built forecasting and reporting systems for ecommerce leadership, including automated reporting workflows and holiday demand forecasting that improved decision speed and reduced manual effort.
Credit modeling, regulated data
Developed production credit models and worked with sensitive consumer data in a regulated environment, combining statistical rigor with practical implementation.
AI-supported operations
Designed and implemented AI-supported estimation and intake workflows, connecting website intake, operational logic, and CRM delivery into a usable day-to-day system.
I do my best work on messy, real business problems where analysis and implementation stay close together. I like building durable systems, reducing manual work, clarifying decisions, and turning rough workflows into something a team can actually use.
From June 2021 through December 2025, I took a planned career break focused on primary family caregiving, independent research, and continued technical development. During that period I stayed hands-on through self-hosted systems, automation work, and ongoing study across analytics, infrastructure, and digital-asset market structure.
Primarily remote. Open to the right in-person or hybrid opportunity in Parkland / South Florida, Coppell / DFW, and possibly Reno / nearby.
Work involving SQL, Python, bash, forecasting, analytics, workflow automation, internal tools, or decision-support systems.
This assistant answers questions based on my resume and project summaries.