Hey! I’m Cynthia, a Machine Learning Engineer who helps data scientists write better code.

I’ve spent the last 5 years working my way from Data Analyst → Data Engineer → Software Engineer → ML Engineer.

My Journey:

  • Started as a Data Scientist at Discover Financial Services (2020)
  • Moved into MLOps at Arity, building scalable data pipelines
  • Now building computer vision systems at General Atomics-CCRi
  • Along the way: spoke at PyOhio, PyData Virginia, and PyTexas
  • Mentored 20+ data professionals through Springboard, Masterschool, and The Coding School

The Gap I’m Trying to Fill:

Most data scientists learn pandas, sklearn, and maybe PyTorch. But nobody teaches you:

  • How to write production-quality code
  • How to deploy models that don’t crash at 3 AM
  • How to collaborate with software engineers without feeling lost
  • How to transition from “I can build a model” to “I can ship a model”

That’s what this blog is about.

Who This Blog is For:

  • Data scientists who want to level up their SWE skills
  • ML practitioners transitioning to MLOps or MLE roles
  • Bootcamp grads and self-taught folks without a CS background
  • Anyone who wants to level up their data skills

What You’ll Learn:

  • Software engineering fundamentals (logging, testing, version control)
  • MLOps essentials (Docker, CI/CD, model deployment)
  • Career advice from someone who just did the transition
  • Real-world lessons from building ML systems in production

I’m here to give you the SWE skills that’ll make you a better ML practitioner, and more valuable to employers.

📧 Want personalized career coaching? Email me at cynthia@cynscode.com

🎓 Free Resource: Grab my SWE Checklist for Data Scientists to start leveling up today.