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Learner Spotlight: My Journey From Cybersecurity Professional to Data Analyst [Testimonial]

Q&A with Patrick Kelly, Professional Data Wrangler

Can you tell us about your background?

My career began in 2010 in the Air Force working in the field of Security Forces, more commonly known as Military Police. I was involved in physically securing government facilities in South Korea and Japan, and even got to guard Obama’s plane once! After leaving the Air Force, I worked in Telecommunications for a number of years as a help desk analyst before moving on to Cybersecurity in the banking domain.

Despite not working in a role that required data skills, I always tried to use them wherever I found myself working, occasionally to the annoyance of my boss, who told me “stick to your day job” 😂. However, there were many times where being the team’s “data guy” was helpful in these roles, like generating informative Tableau reports for management, finding unused data and putting it to use, and identifying insights that were not fully realized before advanced analysis.

More recently, I’ve gained a proper job as a data analyst on a data science team where I finally get to put these skills to use everyday. I found myself unemployed during the pandemic in November 2020 and saw this as a good chance to make a big career change to work with data full time. I went from cybersecurity analyst in banking to data analyst in the publishing industry. DataCamp helped me gain skills that made me marketable enough to be able to make this career move and I plan to move to a data scientist role in the very near future!

I studied software development in school, but I’m a very big proponent of teaching myself the relevant skills I need online rather than throwing money at Higher Ed. I’ve found great value in free or affordable online resources like DataCamp. On the personal side, I enjoy participating in competitions on DrivenData.com and Kaggle, studying Japanese, playing guitar, and of course, knocking out modules on DataCamp.

Around how much time do you dedicate to learning on DataCamp?

About 2-3 hours a day.

How did you find DataCamp and why did you choose our platform over other online learning platforms?

It’s been so long that I can't really remember how I found DataCamp. More than likely, I was just searching for data science learning resources. I do remember checking out DataQuest, and I didn’t go with them because their UI kind of hurt my brain. On DataCamp, everything is laid out in a very minimal and consistent way. It’s very easy to find what I’m looking for.

How has DataCamp positioned you to meet your professional goals?

My new job mostly involves writing Python code. Code that wrangles, cleans, and gets data from point A to point B. Sometimes some SQL gets thrown in the mix, and DataCamp has provided 98% of all my real-world SQL knowledge and education that I couldn’t gain from my previous employment. DataCamp has certainly made my new job a breeze.

What are the skills you’ve learned on DataCamp that have proven to be most useful?

Oh, that is a difficult one. I would say general machine learning skills. It took me a very long time to wrap my head around scikit-learn and how to do something as simple as using train_test_split(). It was very intimidating at first. After getting a lot of guided repetition in, it all made sense overnight. I continue to learn new tips and tricks on the Machine Learning Scientist with Python career track that I continually apply to my real-world projects.

A great example that I’m proud of is building a spam classifier for Bank of America’s Email Abuse team, within their Security Operations Center. Their job is to analyze suspicious emails that internal employees report to their team. They receive great volume of submissions and many of those are junk (or spam). To help automate the processing of these submissions, I built a Logistic Regression spam filter with an accuracy of 93%. Eventually, this was put into production and saved approximately 200 weekly analyst hours. This allowed their team to focus on more pressing tasks.

In my current job, I’ve recently had to build a complex data pipeline (in Python and SQL) that pulls data from an SFTP server, does intensive data cleaning on it, joins that data on a table from a SQL Server database, then forwards the end result to Jira. DataCamp’s course Writing Efficient Python Code helped me make this script 10 times faster and the SQL Fundamentals skill track really helped with the SQL portion of this script.

Currently, I’m working on the Disaster Tweet Competion on Kaggle. To assist with building my solution, I’m going through the Natural Language Processing in Python skill track for guidance while simultaneously applying these concepts to the Kaggle project.

What do you most like about DataCamp?

The relevancy, variety, and quality of courses. On relevancy: Many of the courses age well. After three years, I still look back on some of the older courses for help.

Do you have any advice for someone just starting out with DataCamp?

Think of a data project that you’d like to do in real life, then identify what skills you need to do that project, then look on DataCamp for a course on that skill. Complete that course and then give that project a shot.

For new learners who don’t know where to start, begin with one of the career tracks that pique your initial interest. Then pivot to something else as you learn what is out there! 😊

I also recommend checking out DataCamp’s webinars, which have exposed me to many great minds in the field of data science.

Looking for a community of data enthusiasts for support in your learning journey? Join the DataCamp Slack Community, tell the world you’re a data enthusiast with a custom LinkedIn cover image, and connect with Patrick on LinkedIn.