Jonathan Brownstein

Function as both Data Scientist and Data & ML Architect in the Data Analytics Office, building scalable, production-grade analytics and machine learning solutions for actuarial, finance, and enterprise data platforms.

• Architected and delivered an automated ARIMA-based forecasting platform to predict Net Amount at Risk (NAR), enabling early anomaly detection and proactive actuarial decision-making.
• Designed and operationalized classification-based machine learning solutions to modernize the Same-As-Link (SAL) process, materially improving accuracy, consistency, and data governance; work received formal recognition from the former CEO.
• Built enterprise-grade statistical outlier detection frameworks leveraging Probability Density Function (PDF) theory to identify large-scale attribute shifts and prevent downstream actuarial escalations.
• Led the design of reusable enterprise data assets, including the Field Inventory Report, a comprehensive metadata and data-lineage architecture that became the authoritative reference for the enterprise SDW.
• Developed the organization's first valuation extract comparison architecture, enabling scalable, repeatable deep-dive analysis of valuation movements across time and data sources.
• Serve as technical lead and architecture owner, partnering closely with data engineering, BI, actuarial, and governance teams to ensure analytics and ML solutions are scalable, compliant, and production-ready, aligning delivery with enterprise data strategy.

• Led cross-functional analytics and reporting modernization initiatives, partnering with HR, Sales, Marketing, and Executive Leadership.
• Designed automated reporting frameworks that improved data accessibility, consistency, and operational efficiency.
• Served as a bridge between business stakeholders and technical teams, establishing the foundation for later enterprise data and architecture leadership.