From Meteorologist to Data Scientist in Six Months
Armed with a strong science background but faced with limited career options, Isaac Pato dropped everything for six months and built up a skillset that landed him a job in the data science field.
“I went to school for meteorology and I graduated in 2012. I worked in meteorology for about a year, and then I worked in nonprofit management for three years after that,” said Isaac. “I had a background in sailing as well, but I had this strong science background and I wanted to figure out a way to apply it in a way that was more marketable and would open up more opportunities for me than meteorology. I have a passion for it, but it’s a real niche thing.”
After attending a free introductory data science workshop in Boston and deciding he would pursue it further, a family friend suggested he try Dataquest as a way to learn Python, SQL and applied statistics. Soon after, he relocated from the east to west coast with his girlfriend, and committed to studying full-time while he looked for work. Isaac worked his way through Dataquest’s courses, and explored courses on Coursera taught by PWC and Duke University, as well as courses by Microsoft.
“For me, Dataquest was great because it was all hands-on projects — there weren’t any videos, so I could just read through and go at my own pace,” he said. “I felt that starting from the very basics of Python was a great place to start. I had a little bit of a programming background because I had a very basic C course in college, but it had been like five years. I felt like I was able to hit the ground rolling with that.”
Isaac created a plan and structured his days as if he were attending each class in person. He also included research and supplemental reading in his day, learning how companies can fall in a spectrum from leading the way and using up-to-date tools like machine learning on one end, to using legacy systems like SQL on the other.
Applying For Data Science Jobs
When he felt he was ready to start applying for jobs, Isaac said, the skills he’d learned at Dataquest went front-and-center on his resume.
“I found that I actually got a lot more responses to my resumes than I expected,” he said. “Part of that might be the economy, but I worked with a career counselor and he and I talked a lot about my resume. I kept it very short, very sweet, and specifically laid out the skills I had gained from Dataquest — Python, pandas, seaborn, etc.”
After six months of online learning and honing his resume, Isaac had developed a strong technical foundation, and he found a temporary position working with Cirium, a data analytics firm based in Portland, OR that serves the aerospace industry. He started out doing basic analytics, but after four months, his skills had made such an impact that he was offered a full-time position as a data science quality engineer.
“I think that the skills that most prepared me to do the work there were SQL, and to a somewhat lesser extent Python,” he said. “That’s really what was able to impress them.”
Isaac describes his role as a mixture of analytics and quality assurance (QA). On a daily basis, he mostly runs database queries and performs analytics to determine if the company is communicating high-quality data. He also does some analysis for different parts of the business, including ad-hoc requests for specific details about metrics he’s monitoring.
Combining the technical training he got from Dataquest with some of the business knowledge he found on Coursera, Isaac says he is able to frame FlightGlobal’s data in a larger, more insightful context.
“I was able to communicate actionable insights and try to drill into specific business problems that could make a measurable impact,” he said. “I think that that, along with the hard skills I learned, was really essential for me getting that offer and getting a job at a place that I really enjoy. I feel that I’m on a good track in my career.”
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