How I got here, and why I build what I build.

I am a quantitative analyst who became a builder, who became the person setting the vision — and who never stopped doing the work. Today I lead the investment analytics function for Northwestern Mutual’s $130B Public Investments department: I define the data strategy, set the platform roadmap, sit on the firm’s AI committees, and built the team that ships the in-house Snowflake / dbt / Streamlit framework powering research, trading, and portfolio management for 70+ users. I am, by training, a CFA Charterholder with a Master of Science in Computational Finance and Risk Management. By temperament I am the person who would rather build the right spreadsheet than reformat the wrong one.

I started in equity research at T. Rowe Price covering software companies during the early years of cloud computing — close enough to investment decisions to understand what analysts actually need, and close enough to spreadsheets to understand what tooling they actually use. From there I joined the State of Wisconsin Investment Board, where I spent nearly a decade in the Asset & Risk Allocation division pioneering original quantitative strategies in R as a founding member of SWIB’s AI team, then managing the modernization of the firm’s custom fund-level risk model used by Investment Committee on the $100B+ public fund.

The thread through all of it is the same: an investment team is only as good as the data and tools it trusts. The biggest improvements in decision-making rarely come from a more sophisticated model. They come from removing the friction between a portfolio manager and the question she is actually trying to answer. That is the work I find most interesting, and it is the work I optimize for.

The unusual part of my profile is that I do both halves of the job. I sit at the Investment Committee table and define how the firm uses AI; I also write the dbt models, design the Streamlit framework, and review the code my team ships. Most VPs stop at the first half because they have to. I’ve been deliberate about not losing touch with the second — because the people who can do both are exactly the people I want on my own team, and I refuse to ask of them what I won’t do myself.

The CFA, the MSCF, and a willingness to write code at three layers of the stack are, in combination, less common than any of them in isolation. I lean on that intersection often — when explaining a model to a portfolio manager, when arguing for a database design with an engineer, when interviewing analysts who can do one of those things but not the other two. The right people for this work usually come from one tribe and have quietly taught themselves the others.

I live in Milwaukee with my family. When I am not building things at work I am usually reading, on a long walk, or thinking about how the next generation of investment teams will use AI without losing the fundamentals.