Sales, renewals, and fundraising — all won with something I built.
I build the machine that makes a CS team bigger than its headcount.
I’ve spent my career in the seams between functions, as a chief of staff, a product analyst, and a founding director of data science. What I build helps other teams succeed: the case studies a CEO used to chase a key renewal worth 11% of ARR, the GTM engine that grew top-of-funnel by 400%, and the analysis a C-suite used to close its Series B.
How I Work
Building the system is easy.
Keeping it running is the hard part.
I judge my work by what is still running after I leave. At Keywell that is a CRM migration I ran with an agent I built, a resume screen that took 50+ hours of manual review off the calendar, the first product manager the company hired, and an operating rhythm that outlasted my last day. Handing someone a document is not the same as handing them a system. I build for the person who inherits it.
Roles
Where I fit on your org chart.
CS Operations
I’ve run the operations behind a customer success team: the enablement assets, the renewal motions, the account data. As chief of staff for customer success at Keywell, I secured the new SOWs with existing accounts that grew revenue by over 40%.
Revenue Operations
I treat customer friction as a revenue problem. At FlagshipRTL I built the data-driven case that kept a key account from churning and preserved 11% of ARR. I don’t stop at the save — I trace the friction back to the process that produced it, so the next save isn’t needed.
Business Operations
I drop into complex environments, assess quickly, and execute. As a chief of staff I built the systems, processes, and internal AI agents an AI-native startup needed to scale. The through-line of my career is turning ad hoc work into process.
Experience
The titles changed. The job didn’t.
Chief of staff, analytics lead, founding director — every one of these was an operations job: find the blind spot, build the process, tie it to revenue.
2025 – present
Founder
Powered Analysis is my education laboratory where I experiment with what’s actually worth teaching about AI and data. It’s thought leadership, not an exit.
2025 – 2026
Chief of Staff & CS Lead
The voice of the customer for Keywell’s AI product launch. Oversaw Keywell’s enablement assets and secured new SOWs with existing accounts that grew revenue by over 40%.
2025
Analytics Lead
I came in to help retain a key customer in danger of churning, and I delivered the data-driven case studies used by the CEO to fight for their renewal and preserve 11% of ARR.
2022 – 2025
Founding Director of Data Science
I designed the analysis that got the first FDA approval of an AI algorithm to predict breast cancer risk. I taught our C-suite what the numbers meant, so they could close our Series B.
2020 – 2026
Data Science Instructor
University of Pennsylvania; George Washington Univ.
I started teaching before ChatGPT, and finished as an evangelist for AI. Proud to be one of the first faculty to treat AI as a learning objective, not a tool to be shunned.
2015 – 2022
PhD, Political Science
University of Pennsylvania
Spent years digging deeply into why a job training program with gold-tier benefits went almost entirely unused. It was my first enablement problem, and I’ve been working on versions of it ever since.
In practice
The ideas on this page have a syllabus.
I say retention is a system for moving people up the pyramid. Here is that machinery, built and shipped: a course that takes an operator from wary of data to fluent in it — the same climb I build for customers, productized end to end.
ONLINE course
Practical Data Analysis for the Modern Professional
Analysis isn’t about technique. It’s about judgment — and you can learn judgment. In under two hours, with no code and no math, I teach professionals to ask the right questions of any analysis, challenge the assumptions underneath it, and treat AI as an analyst whose work they know how to check.
The Data Analyst Mindset
5:34
Measurement
19:52
Randomization and Selection Bias
10:18
Correlation vs. Causation
19:54
Sample Size, Variance, and Uncertainty
13:00
Missing Data and Outliers
12:05
Data Visualization
21:24
Get in touch
I’m exploring customer success, revenue, and business operations roles. The fastest way to reach me is a 30-minute call.