Professional Summary
Strategic AI Architect and Technical Leader with 12 years of experience driving enterprise-level analytics and AI transformation. Partner for technical and business executives to identify, quantify, and deliver practical value through AI solutions — from foundational automations to fully agentic workflows. Expert at bridging the gap between complex data science and executive-level business value through governance and a product-focused mindset.
May 2014 – Present Decade-plus of leadership progression through Marketing Analytics, BI, and AI.
Lead AI & Agentic Solutions Architect
(Lead BI Developer) | Dec 2023 – Present
Enterprise lead driving change from BI to agentic AI systems and governed engineering standards.
- Strategic AI Consulting: Serve as a cross-functional thought leader, providing technical expertise and strategic guidance to 14 business units seeking to develop and implement production-ready AI solutions across the organization.
- Technical Governance: Established the organization’s first AI, Python, and Power Platform governance frameworks. Transformed a decentralized development culture into unified CI/CD workflows, reducing failures and standardizing code quality across 10 engineers and 250+ citizen developers.
- AI Orchestration: Architected “CommentGPT,” Uline’s first enterprise AI agent analyzing 2M+ annual customer comments in near-real time. Reduced time to identification of critical shortcomings across product, service, shipping, and technology by 98% (two days to one hour) and provided a lift in caught issues by over 31%.
- RAG Architecture: Deployed a production-scale RAG architecture handling 2.5M annual customer service procedure queries. Reduced employee time-to-answer by 73% and decreased internal helpline escalations by providing instant, cited answers across the knowledge base.
Senior Business Intelligence Developer
Mar 2021 – Dec 2023
Senior-level technical lead specializing in custom Python, Power Platform, and ML-driven automation.
- Enterprise AI Roadmap: Spearheaded the organization’s initial enterprise AI roadmap. Designed and socialized early Proof of Concepts using Azure OpenAI, securing executive buy-in and budget for the establishment of the current AI function.
- Operational Efficiency & AI Readiness: Developed Python-based productivity tools reducing Data Warehouse discovery timelines by 66% (from 3 months to 1), accelerating enterprise data readiness for AI.
- Strategic Data Governance: Key voice on the Data Steward Steering Committee, bridging the gap between IT and Business leadership to define data standards required for ML/AI adoption.
- Machine Learning Implementation: Engineered production NLP classification models, automating manual workflows reclaiming 1,200+ annualized hours for high-value analysis.
Database Marketing Manager
Jan 2018 – Mar 2021
Head of Analytics for a $500M marketing budget, reporting directly to VP of Customer Development.
- Organizational Leadership: Managed the centralized analytics function supporting a 100-person department. Recruited and developed a high-performing team of 5 analysts, establishing rigorous ROI reporting standards.
- Technical Strategy: Identified a critical gap in vendor capabilities and self-architected internal automation pipelines using R and Python to support acquisition goals.
Digital Advertising/Marketing Analyst
May 2014 – Dec 2017
Technical analyst managing financial optimization and predictive analytics.
- Financial Optimization: Optimized over $9.5 million in annual digital advertising spend using budget optimization models built with linear programming.
- Predictive Analytics: Implemented several machine learning models influencing marketing decisions including customer churn, expected lifetime value, and market basket analysis.
Selected Technical Consulting
J&J Consulting Inc.
Nov 2019 – Feb 2021
Data science consultancy delivering end-to-end predictive analytics for private clients.
President / Principal Consultant
- Strategic Solution Delivery: Translated abstract business problems into concrete technical requirements, delivering production-ready code that automated manual analytical workflows and allowed employees to focus on high-value human interactions rather than data entry.
- Full-Stack Data Science: Built complete predictive analytics pipelines using Azure ML, Python, SQL, and Git, managing the full development lifecycle from data ingestion to deployment.