When Carly Taylor founded Rebel Data Science, the name was a statement. Boutique consulting firms for gaming ML don't typically position themselves as acts of rebellion. This one did - because the rebellion is the point.
The gaming industry has a talent pipeline problem that starts well before the job applications arrive. Women and non-binary individuals are systematically steered away from data science careers through a combination of culture, access, and the quiet discouragement of not seeing people who look like you doing the work.
Rebel Data Science exists to break that pattern. Taylor brings authentic AI education - the kind that doesn't assume you have a CS degree, a prestigious pedigree, or the right contacts - to individuals and brands who need it most. The consulting is real. The mission is realer.
Most newsletters about data science and ML read like documentation. Taylor on Tech reads like advice from someone who has actually done the work and survived the learning curve.
Carly Taylor's newsletter covers the intersection of data science, machine learning, and the gaming industry - a niche that turns out to have enormous crossover appeal. The ML techniques that make games smarter are the same ones transforming enterprise analytics. Taylor connects those dots in plain language.
With 100k+ LinkedIn followers who tune in for her takes on everything from player behavior modeling to career navigation in tech, her newsletter is the natural extension of a voice that doesn't sugarcoat what the industry actually looks like.
Most ML engineers come up through CS programs. Carly Taylor came through computational quantum dynamics - a field where you model the behavior of systems you can't directly observe, using mathematics to predict outcomes that only become visible at scale. That training isn't a footnote. It's the lens through which she approaches every player behavior problem.
Gaming isn't just another vertical for Taylor - it's the vertical she's spent years arguing deserves more serious analytical investment. Player behavior data is among the richest behavioral datasets that exist. Real-time feedback loops, massive sample sizes, clear outcome metrics. She makes the case that gaming ML is a preview of where enterprise AI is going.
Taylor doesn't save her DEI work for off-hours. Her content, her company, and her consulting all carry the same message: data science needs different people thinking about different problems. When 100k+ LinkedIn followers show up for her takes, they're getting both the ML knowledge and the point of view that comes with being someone the industry wasn't designed for.
- Two non-provisional machine learning patents - documented proof of original technical contribution
- Player churn prediction model at Activision: 17% reduction in attrition, 22% revenue increase
- Multiple peer-reviewed publications in computational chemistry and ML
- Speaker at Databricks Data + AI Summit 2025 - the central gathering of the modern data stack community
- Featured on Women in Data Podcast, 365 Data Science, AtScale Podcast, and multiple ML-focused shows
- Fireside chat with Matt Turck, Partner at FirstMark - the VC world paying attention to gaming ML
- 100k+ LinkedIn followers - one of the most-followed data scientists creating gaming-focused content
- Founded Rebel Data Science with explicit mission to diversify data science talent pipelines
- Created Taylor on Tech newsletter as an accessible entry point to serious ML thinking
- Active GitHub presence with public ML projects including deep learning for organic chemistry
- Advocates for women and non-binary individuals in data science through speaking, writing, and consulting
"Gamers paved the way for AI."
Chain of Thought / Galileo AI Podcast
"Treat game data as a first-class citizen."
Databricks Data + AI Summit
"Making data science more accessible and opening doors for underrepresented groups to find fulfilling careers in tech."
Rebel Data Science Mission