A decade of building, leading, and advising on AI and data

Technical presales · Generative & agentic AI

Customer-facing technical lead for enterprise accounts. I owned the solution strategy across sales cycles, designed generative and agentic AI use cases, and ran the enablement that turned them into adopted, growing workloads.

• Owned the technical strategy across enterprise sales cycles with Account Executives, identifying new workloads and guiding validated solution designs from discovery through adoption. Helped drive 20%+ YOY consumption growth across every account in the portfolio.
• Led end-to-end solution design for high-priority generative AI use cases, including RAG, intelligent document processing and extraction, and AI agents, covering ingestion, retrieval, orchestration, application integration, security, scalability, and cost.
• Advised enterprise customers on data and AI strategy, mapping business priorities, technical constraints, and security requirements to reference architectures and sequenced adoption roadmaps.
• Led enterprise proofs of concept and delivered 25+ customer-specific demos, hands-on labs, and enablement sessions using customer data across Cortex AI, Document AI, and Snowflake ML.
• Contributed to $5M in renewal ACV through technical risk assessments, architecture reviews, and executive presentations that connected platform capabilities to business value.
• Architected agentic systems using Cortex Agents, tool calling, and multi-step LLM orchestration, with semantic models for NL-to-SQL and Snowflake-managed MCP servers that securely connected enterprise data and tools to external AI agents.

Team leadership · AI strategy · MLOps

Led a data science team and advised senior leadership on AI strategy, governance, and where machine learning could move the business.

• Managed a team of 4 data scientists and analysts delivering AI/ML models that generated $20M+ in revenue across sales, operations, and customer engagement.
• Advised senior leadership on AI strategy and established best practices for model monitoring, governance, and MLOps.
• Led enterprise-wide AI initiatives spanning data governance, third-party technology evaluations, and data monetization strategy.

Production ML · Forecasting · Real-time scoring

Built and deployed the forecasting and optimization models behind audience and advertising decisions, and modernized how models reached production.

• Built audience forecasting and programmatic ad-optimization systems that increased prediction accuracy by 400% and drove $15M in incremental revenue.
• Led the transition from batch inference to real-time scoring, improving model efficiency by 60% and giving business teams faster access to outputs.
• Designed ML pipelines in Azure Databricks, Snowflake, and MLflow that standardized deployment and established a repeatable MLOps foundation.

Analytics leadership · Decision frameworks

Defined the metrics and analyses that digital product and marketing teams used to make decisions.

• Defined KPIs for digital products and built data-driven decision frameworks adopted across multiple business lines.
• Built customer segmentation analyses that improved marketing targeting and conversion across key segments.
• Partnered cross-functionally to embed data insights into day-to-day business operations.

Fraud analytics · BI for enterprise clients

Used analytics and BI to trace fraud and deliver decision tools to some of the largest retailers in the country.

• Used Random Forest feature importance and Tableau to pinpoint the origin of fraudulent activity across enterprise portfolios, informing a mitigation strategy that cut fraud losses by $2M per month.
• Built interactive BI applications for Fortune 500 retailers including Walmart, Kroger, and Nordstrom using R and Shiny.