Jaxen Wood is Head of Operations and Senior Data Scientist at SwiftFox and The Red Fox Group. (He is also, probably, the loveliest person you’ve ever met)
So Jaxen, what’s your job? And, what does a regular day look like for you?
As Head of Operations, and also Senior Data Scientist, every day is different as I jump between those two responsibilities. As Senior Data Scientist, I’m working with clients on data projects, helping them solve organisational problems, helping to increase their sales, or uncover valuable insights. Some projects might take weeks where I’m cleaning, analysing, comparing and reporting on a clients datasets. When I’m in the Operations mindset, I’m often doing very similar things, but with our company as the client. This can involve setting up automatic reports for system usage, analysing metrics across our services, and identifying opportunities from these insights.
What’s the best part of your job?
Revealing a piece of intelligence from a client’s data, or even our own, is always a very satisfying moment. Often while working on a data project, the client may have a certain number of ideas about the data we are about to explore. As the team and I start digging into the data, comparing it to public datasets and analysing the results, we often find insights about the clients business they weren’t even aware of. These insights can help target the correct groups of people, or advertise in the right places, or better understand their market. All businesses have data, and most don’t have the time to fully investigate it. Being able to deliver that service to clients is always something I look forward to.
“Think outside the box when analysing different datasets … you’ll often need to think of unique ways to find a pattern.”
Okay, now what are your top tips for aspiring data scientists?
Think outside the box – when analysing different datasets, and looking for various insights, you’ll often need to think of unique ways to find the pattern. When we were helping a cultural institution analyse their attendance rates, we were struggling to determine why some t some dates had a skyrocketing numbers of guests, and others had very few. We looked at promotional events, holidays – but we couldn’t find a clear explanation. Suddenly we thought to overlay historical temperature data, and we found a correlation between warmer days and fewer attendance. In short, we found that the weather could help predict attendance – an insight we wouldn’t have had, if we hadn’t thought outside the box.
“Don’t stress if you can’t code finding insights from data isn’t about coding, coding just makes things easier and quicker.”
Don’t stress if you can’t code – finding insights from data isn’t about coding, coding just makes things easier and quicker. Excel has plenty of tools to allow you to analyse a dataset and investigate a possible pattern. As you start getting into bigger and bigger datasets, and wanting to compare multiple datasets at once, you may quickly hit the limitations of Excel, and need to find the tool that’s right for you. Examples are SQL or Jupyter Notebooks, which allow you to compare multiple datasets and other really cool things.
Get started with something interesting – there are so many public datasets online that can be really interesting to delve into. The federal government, and each state government have data websites full of public releases of datasets across their departments. You can find the number of dogs registered in each postcode across Brisbane. Or the number of people flying out of each airport each month. Or daily rainfall data for locations right across Australia going back decades. This data is super easy to use, and allows you to start experiencing large datasets within the tools of your choice.