Engineering Culture & Leadership

As the first ML Engineer in the region, my role wasn’t just about code—it was about culture.

Bridging the Gap

Data Scientists are excellent at statistics but often lack software engineering rigour. My goal was to bridge this gap without stifling creativity.

Initiatives

• RFC Process: We implemented a “Request for Comments” process for all major architectural decisions.
• Pair Programming: Weekly sessions where engineers and scientists pair up to refactor notebook code into production-grade modules.
• Post-Mortems: Blameless retrospectives for every production incident.

“Culture is what happens when you’re not in the room.”

By establishing these practices, we scaled from 1 to 4 distributed squads while maintaining code quality.