Resume

• Led Revenue Operations and company-wide data initiatives through ARR growth from $6M to $30M, supporting new sales, expansion revenue, and customer retention.
• Owned 20+ major business systems and integrations, including Salesforce, Zendesk, Planhat, Ordway, and related revenue, customer, and finance platforms.
• Built pipelines, automations, and integrations that connected Salesforce, billing, customer success, marketing, finance, and product data for reporting and operations.
• Replaced manual monthly revenue reporting with automated daily reporting, giving leaders a more granular view of revenue movement, customer activity, and business trends.
• Managed ETL, storage, data modeling, and analytics workflows for billions of data points across thousands of datasets.
• Built dozens of executive and functional dashboards, reports, and metrics for leaders across sales, customer success, marketing, finance, and the executive team.
• Improved go-to-market systems and data workflows behind thousands of monthly leads and hundreds of new deals.
• Administered core business systems used by hundreds of employees and helped teams get cleaner data, better reporting, and more reliable processes.

• Built and maintained operational processes for managing financial data across internal systems.
• Improved data accuracy, workflow consistency, and reporting reliability for finance and operations stakeholders.
• Partnered with cross-functional teams to identify process gaps, automate manual workflows, and create more scalable operating systems.
• Supported the transition from manual operational processes to more structured, data-driven business systems.

• Built, deployed, and maintained machine learning models on AWS to predict customer longevity, churn risk, SEO performance features, and related business metrics.
• Used statistical modeling and data analysis to identify patterns in customer behavior and support business decision-making.
• Developed data workflows and analytical outputs using Python, SQL, and cloud-based infrastructure.
• Partnered with stakeholders to translate business questions into predictive models and actionable insights.

Thesis: Comparison and Assessment of the Extremes of Different Types of Climate Model Simulations

Thesis: Gaussian Process Modeling of Modern Mass Spectrometry Computer Experimental Data