Zachary Goldman

Intro

I’ve always been driven by curiosity and a desire to solve meaningful problems. That’s taken me on an unconventional path—from studying religion in a monastery to performing stand-up comedy, shadowing surgeons, and building tools that help millions of users. At Microsoft AI, I’ve driven measurable results like leading Copilot metrics for the entire Edge org, improving retention of a feature by 5x, and scaling experimentation systems. Beyond tech, I’ve tried to explore life deeply: finessing my way into the Library of Congress with an email receipt to research PM methods when it was closed, building ML models to predict satisfaction based on college major choice, and coding tools for students and nonprofits. Exploring different career paths has helped me get better at being a beginner and building from first principles, and I love finding creative ways to get around obstacles (e.g. convincing marketing to market a feature before it was shipped then leveraging the campaign to get it shipped in the first place).

About Me:

• Exploring Problems That Matter After interning for a congressman, I loved the scope of politics, but wanted something with more immediate impact, which led me to shadowing a surgeon and ear nose throat doctor. After helping with over a hundred patient consultations and 5 surgeries I realized I wanted a field with more trial and error day to day, so I explored a law firm internship, then a consulting internship at Deloitte Digital which taught me I wanted to be implementing rather than just recommending.
• Learning to Build Through Iteration Around this time, I read the Sprint Book by Jake Knapp detailing Google Venture's one-week sprint process to help startups falsify hypotheses to create meaningful products. Inspired, I presented a workshop on the Design Sprint to Deloitte’s partners, and started building projects (many of which you can check out below!). In particular, as someone who'd worked as a counselor at a camp for folks with housing instability and cold-called for the American Cancer Society previously, I felt there was a lot of potential in applying computation and data to social impact areas that often lacked data rigor. I worked with CARE Somalia to build sites for medical staff to track maternity visits, and revamped the Rutgers Career Office's code-base, giving them one-pager data on specific majors to help families in their consultations. I then made ML models for my senior thesis predicting satisfaction based on experiences in college and major, alongside investigating reasons for choosing a major.
• Driving Impact at Microsoft AI For about the last year and a half I've been fortunate to explore my passions of experimentation, structured thinking, and impactful AI work at Microsoft AI, where I've worked on feature work, metrics, experimentation, and user research (see below). Together, I've been building a skillset of data-informed product decision making.