Top 5 Career Paths for Data Professionals: Machine Learning, Machine Learning Engineering, & Data Science

The large scale use of data is relatively new and we’re inventing stuff as we go. Different organizations have different data cultures, and there are many strange evolutionary forces at work. This can make it very confusing to get started on a machine learning career.

For example, my titles have included: researcher, applied researcher, program manager, applied research manager, principal software engineer, architect, machine learning scientist, and software engineering manager. And over the past 15 years I’ve worked with: data scientists, decision scientists, data analyst, machine learning engineers, data quality engineers, scientists, applied scientists, research scientists, and ranking engineers. And all of these titles were doing similar data and ML focused work.

What should you search for when looking for a machine learning job? Or a data science job?

This video will introduce five key professional data functions: what they are, core skills, and how to get started. These include:

• Machine Learning Researcher
• Data Scientist
• Machine Learning Scientist (Modeler)
• Machine Learning Engineer
• Machine Learning Architect (Product Manager or Program Manager)

The point is: when you’re looking for a job in data or machine learning, keep an open mind – don’t get over-indexed on a particular title or a particular way of looking at the field.

It’s an exciting time to be a data professional. Data and machine learning are making the world a better place – and things are changing fast. Good luck. Keep safe!

To learn more see: https://amzn.to/35Q581h and https://youtu.be/Qz8GhltWeRM