Leading AI Teams in Production Environments
Roger has spent the last decade working with, leading, and managing data science teams and delivering machine learning systems that operate at enterprise scale. As a Data Science Manager, he led cross-functional teams developing predictive models using advanced techniques including logistic regression, XGBoost, LightGBM, and ensemble decision trees—the same algorithms powering ClearFlow's prediction engine. His experience spans the full lifecycle of AI development: from initial problem framing and model development through production deployment and ongoing optimization. This end-to-end expertise is critical for building systems that don't just work in theory, but perform reliably in real-world operational conditions.
Global Consulting with IBM
As a worldwide consultant with IBM, Roger delivered AI and analytics solutions to enterprise clients across industries, gaining deep insights into how large organizations evaluate, adopt, and operationalize technology. This experience informs ClearFlow's approach to working with municipal utilities—organizations that require proven, enterprise-grade solutions with clear ROI and minimal operational disruption.
Predictive Analytics for Operational Systems
Roger spent five years specializing in predictive analytics for logistics systems—complex, real-time environments where accurate forecasting directly impacts operational efficiency and cost. This background translates directly to wastewater infrastructure: both domains require analyzing continuous sensor streams, accounting for external factors (weather, demand patterns), and delivering actionable predictions with tight time windows.
The convergence of three factors makes this the ideal moment to apply AI to infrastructure management:
1. AI Maturity: Machine learning techniques that were experimental five years ago are now proven, production-ready technologies. Roger's decade of experience deploying these systems means ClearFlow isn't experimenting—it's applying battle-tested methods to a new domain.
2. Data Availability: Modern SCADA systems and IoT sensors generate unprecedented volumes of infrastructure data. For the first time, utilities have the raw material needed for effective predictive modeling. Roger's logistics analytics background prepared him to work with exactly this type of real-time operational data.
3. Regulatory Pressure: Increasing EPA enforcement and climate-driven overflow events are forcing utilities to move beyond reactive maintenance. The regulatory and environmental landscape has created urgent demand for the preventive approach ClearFlow enables. Roger recognized that his unique combination—production AI expertise, operational analytics experience, and understanding of enterprise adoption—positioned him to address a critical infrastructure challenge at exactly the moment the technology and market conditions aligned.
"After 15 years building AI systems for enterprise operations, I saw an opportunity to apply these proven techniques to a problem that impacts communities, waterways, and public health every day. Utilities are managing increasingly complex systems with the same reactive tools they've used for decades. ClearFlow changes that—not with experimental technology, but with production-grade AI that's ready to deploy today."—Roger Welch, Founder & CEO
