This blog is for data science teams and business leaders who work on problems where timing and risk matter. Predictive maintenance, customer retention, credit risk, employee attrition — if you want to build ML models for these, you’re in the right place. Welcome!
I’ll be writing about survival analysis, practical data science, and the tools I’m building to make this work easier.
First up: A preview of my Time-to-event Prediction Guide
Most predictive models answer the wrong question (yes / no):
”Will this customer churn?” ”Will this machine fail?” These sound useful — but what you actually need to know is by when, and how likely. (And later, how can you prevent it.)
Knowing when changes everything. It’s the difference between a maintenance team that reacts to breakdowns and one that prevents them. Between a retention campaign that fires too late and one that catches customers before they’ve already decided to leave.
The techniques exist. The open-source tools exist. What’s been missing is a practical, end-to-end guide that doesn’t skip over the messy parts where real projects actually get stuck.
I’m writing that guide.
Get early access
The preview is available for registered readers. Register to read it now, and you’ll be notified when the full paper is available. Don’t hesitate to reach out or share your thoughts in the comments below. Help me make this blog interactive and educational!