Turning the data financial firms run on into decisions they can act on.

Investment-data leadership shaped by markets, technology, and practical business outcomes.

I build the analytical layer that turns the data financial firms actually run on — market and portfolio data, client and CRM data, sales pipeline activity, and behavioral interaction signals — into decisions the business can act on.

My path started in the Pacific Northwest, where exposure to Russell Investments and the asset-management community sparked an early interest in capital markets and responsible stewardship. At Oregon State, an honors thesis in strategic finance showed me how statistical models could clarify real-world investment decisions. That became the bridge between finance, data science, and machine learning.

Early roles at Threshold Group, Market Street Partners, and Symphony made the opportunity clear: investment organizations were rich in data but often limited by fragmented systems, manual reporting, and heuristic decision-making. I began building the data foundations, analytics tools, forecasting systems, and executive reporting layers that gave leaders better visibility into portfolios, clients, distribution, and risk.

Since then, my work has expanded across a $20B credit platform, a $1.2T asset manager, enterprise technology, and commercial investment-software products. At LinkedIn, I build enterprise decision-intelligence systems on Databricks across large-scale business data; at Amazon, I modernized analytics infrastructure for high-volume hiring; at Osyte, I designed private-markets forecasting capabilities now embedded in a commercial investment-technology product. I am most energized by roles where AI, analytics, and human judgment come together to improve decisions, create efficiency, and deliver better client outcomes.

Outside work, family is central to who I am. I enjoy traveling, skiing, astronomy, running, hiking, and time outdoors with my wife and two sons.