Get to know our newest team member, Taylor Perkins!

I was born in Indiana and moved to Tennessee at the beginning of the 6th grade. With that being said, I call Nashville my home and the city I grew up in. In high school I really wasn't interested in software (unless video games count), but I was interested in music instead. A year after I graduated high school I decided to pursue a career in guitar building and repair since it would bring me closer to music. After a couple years in the industry, I decided it wasn't everything I was looking for in a career. At the time, I had a few friends in the data science industry that served as mentors and gave me an introduction to the life of a data scientist. I decided that the software industry could be the next step, so I switched careers and went into the tech field.

In January 2017, I left my job as a repair tech and went full force into studying web development at Nashville Software School (NSS). The course was a 6-month bootcamp during normal work hours with material ranging from Javascript and frontend web design to a Python backend using Django. NSS didn't have a data science curriculum at the time, but I knew Python was the language of choice for many data scientists. So even if I went into web applications, I knew I would be inching closer to the data science industry through this common programming language. The course paid off and landed me a job as a backend engineer at icitizen in Nashville. At icitizen, I had the opportunity to work under three very senior software engineers. They taught me about API design and architecture, testing code, and databases. During this job, I found out that I really enjoy structure in code and building from the ground up.

During my first few months at icitizen, NSS reached out to me to let me know that they would be starting their first ever Data Science bootcamp and asked if I would join as a guinea pig. This was a big decision for me since I was now working full time as a backend engineer and the 9-month course would take up my Tuesday and Thursday nights as well as Saturday days, not to mention all of the hours studying or working on projects. However, this field introduced me to software engineering to begin with, and I had to take a leap to find out if it was something I would be passionate about. In the end, I agreed to take the course.

There was a lot of ground covered in this course over the span of three sections. We started out with some python basics using pandas. There were many projects around data manipulation and data visualization using pandas, matplotlib, seaborn, and others. The second section focused on a lot of the same principles, but with R as the primary language. At the end of this section, we worked on a "midstone" project that showcased everything we had learned up to this point. My project was on analyzing song characteristics given by Spotify for the top 100 songs from the Billboards chart every week for the past year. In final section we went back to python to focus on modeling techniques and predictive analytics. Like the midstone, we had a final project to cover this last portion. My main interest in this final section was around NLP, so I wanted to build a project that focused on some of those skills I picked up. The project I came up with was visualizing graphically the relationship between two random chapters from the book "Spoon River Anthology" based on shared words and their synonyms.

Post graduation I found myself with a new love and started searching for a middle ground between data science and software engineering. What are the similarities, and how do they come together? Since I have now finished both the web development course and data science course, I feel like if I am only using one set of skills and not the other then I am not giving my all, and this really messes with me. Given data science’s relatively infant stage across industry segments in Nashville, it was hard deciphering where I could go that would make use of both sides of my skillset.

Luckily for me, I was offered a position at NSS to help teach the following data science course. This was such an honor to me, and a great opportunity to continue to learn and figure out where I stand in this industry while also helping other students grow in their careers. At the same time I accepted a role as a Data Applications Engineer at Juice Analytics in Nashville. In this role I used python to build applications that allowed companies to better understand their data through a website setting. At Juice and NSS I continued to grow my python skills and at the same time considered my next avenue.

NSS loves to focus on real world problems that companies are actively dealing with (or had previously dealt with) to give to their students as projects to work on through the course. The General® had just such a problem and partnered with NSS to come into the classroom and present it for the students to solve. Through this season as a developer I had been pro-actively trying to figure out ways to blend data science and software engineering, specifically in areas of model deployment. Serendipitously, The General was asking the same questions. After a few great conversations with current team members, I formally interviewed for an open position on their Machine Learning Engineer team.

And here I am – a Machine Learning Engineer with The General and actively "drinking from the firehose" as they say…or rather several firehoses. The AWS firehose is a big one. Understanding how to set up and tear down EMR clusters, EC2 instances, working with S3, and running batch jobs using Zeppelin and Spark. The docker firehose. A few small firehoses here and there around helping create tools and libraries to be used for model training and deployment consistency. There is a small faucet around learning C# to help support one of our data scientists. And lest we forget the biggest firehose: wrapping my head around all of these tools and technologies and learning how they work most efficiently together. Each piece is its own instrument in this orchestra of technologies to perform a symphony of large scale model deployments in a consistent and manageable way that will be used by a massive audience. I am excited to help conduct it all.

So that is professional Taylor! Non-professional Taylor plays music in a REALLY cool band called In Confidence, has spent way too much time playing Rocket League, owns several plants, and will probably own a bar / coffee shop one day.

I have been working at The General for almost two weeks now, and it has been such an amazing ride. The mission is critical, my colleagues are exceptional, and we are doing some great things. Every day I look forward to continue drinking from the firehose.

Taylor Perkins