My name is Katie Baker, and I'm a machine learning and data engineering consultant. At my heart, I'm a problem solver. I love having a new challenge to work on, and data challenges never disappoint.

I've worked in machine learning for over a decade, and it's only gotten more interesting as technology continues to evolve. My career started in the healthcare industry, where I was writing my own modeling frameworks, from neural networks to bayesian classifiers, in Java. This is where I fell in love with scalable production architectures for data engineering and machine learning. I was able to work with some incredible engineers, who taught me data modeling standards and extensible design patterns. After nearly 6 years, I moved on to explore other industries and solve different problems.

The next company I worked for, I realized that there was a big gap between most machine learning teams and the software teams where they were hoping to deploy their models. My value in this role, and a value that I continue to offer to my clients, was to bridge the gap between the data teams, business teams, and the devOps/software teams who needed to approve and consume from these models. I created an ML Ops process that enabled them to deploy their first ever machine learning model through CAB (Change Advisory Board) and into production.

The next opportunity was one that I could not turn down. The chance to build a machine learning and data engineering team with completely green fields at a startup. Having the chance to think about how problems should be solved, without tech debt, was such a luxury, and one I continue to enjoy when working for my client's that are startups.
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After nearly two years in this role, I transitioned into full time consulting. As a consultant, I've been able to continue to support the people and teams that I love working with, while also being able to work on other projects, explore other industries, and, ultimately, solve other problems.