Nina

Hi, my name is Nina and I work within the Enterprise Data Center team @Atlassian, specialising in Behind the Firewall (BTF) product analytics. I recently graduated in 2019 from Curtin University with a Bachelor of Science majoring in Data Science.

A large part of where I am today can be attributed to my time volunteering at Robogals, back in university. Robogals is an international student-run organisation that aims to inspire, engage and empower young women to consider studying engineering and related fields. Its primary activity is interactive, engineering based workshops for girls aged between 8-18. Whilst initially volunteering for a few years, I eventually joined the Robogals Perth committee where I acted as a schools manager for the metropolitan region. I was in charge of organising over 100+ workshops/events to engage girls into STEM fields and even had the opportunity to fly out to a Robogals SINE Asia Pacific conference. If you are at university today, I recommend taking a step out of your comfort zone and try joining a club or organisation such as Robogals. It’s a great way to make new friends, enhance your interpersonal skills and make a real impact on another student’s career journey. More information can be found at https://robogals.org/locations/asia-pacific-apac/.

So here it goes. A snapshot of a day in the life of a graduate product analyst @Atlassian.

8:00 am – Get ready for a new day

Wake up and eat brekkie, make a cuppa of Milo. You get the gist

9:00 am – Start work at home and check messages and updates

I usually start my day off by having a look at any new emails or messages on Slack, to see if there’s any blogs/announcements to read up on. These can range from company-wide announcement to team-specific updates.

9:30 am – Continue some analytics work

As a product analyst, we work on looking at how new features that have been released in a new version of a product have been adopted by our customers. This might include looking at performance, feature churn, adoption and adaption of that new feature. I primarily use Spark SQL, Python or R to produce the analyses to investigate these metrics. We use platforms such as Redash, Databricks or Tableau to do a bunch of these analyses.

12:00 pm – Lunch time

I like to have a quick lunch and then I try to take a walk outside to relax – away from the computer screen! (Unless I take a nap instead…)

1:00 pm – Chat with my supervisor

My awesome supervisor and I have weekly catchups to discuss the work I have been doing recently. I usually use this time to discuss the overall direction of a project, updates on meetings with our stakeholders and code reviews. My supervisor takes this time to provide me with some important feedback points. For example, how to enhance the efficiency of my code or how to improve my engagement with a stakeholder.

2:00 pm – Continue analytics work

Continue analytics work from before and incorporate any feedback points from my supervisor.

3:00 pm – Start writing a page on Confluence

Once the analytics is completed and feedback from my supervisor has been incorporated, I proceed to communicate the findings! Of course, as an Atlassian, we use our own product Confluence to detail what sort of results we found for the new feature. The golden rule in analytics is that we must not only convey the main results from an analysis but also try to tell a conveying story alongside our results.

These blogs are usually for our internal stakeholders – usually product managers and their product teams (e.g. developers, designers). Product managers are the drivers behind a product and much of the analytics we do feed into their decisions and next steps for a product.

4:00 pm – Weekly Product Analytics Team Meeting

We have a product analytics team meeting once every week. This is where product analysts from my team run through the work they are doing or have completed recently. It is mostly for feedback purposes and for all of us to learn new ideas from each other! It is also where we have a chance to be silly with each other, as you can see from the photo.

5:00 pm – Finish up work for the day

I take this time to wrap up the work I have done today. If I have a meeting scheduled with a stakeholder, manager or supervisor for the next day, I try to update our 1:1 page with any topics or links. This way they have some time to look at those things before the start of the meeting the next day.

5:30 pm – Time to finish working

I make sure to turn Slack notifications off, so I have a good rest from work, close my laptop and well…. walk away from my desk (COVID-19 working life be weird).

~ ~ ~

Hope this day in the life article was interesting to read. To be fairly honest, it’s hard to really capture a working life with just one day (selection bias is not just a problem in my analyses! Yes… I had to sneak in at least one lame statistics joke).

To put things into perspective though, I have days where I will be on my computer the whole day chugging out analytics work. I also have days where I’ll be in a few more meetings with developers, designers and product managers. We even have ShipIts or Innovation weeks where we go into teams and work on an innovation new idea and create something different - away from our usual work routine.

If you have any further questions, don’t hesitate to reach out to me on LinkedIn.

Thanks for reading!