Updating Results

Rio Tinto

4.3
  • 50,000 - 100,000 employees

Lincoln Crooks

6.15 AM
 
At this point I am dozing off again after snoozing my alarm for the fifth time before panic quickly sets in realising that I’m running late. After quickly showering & eating breakfast, I’m standing at the bus stop in less than 30 minutes, not bad. 

7.00 AM
 
I make my way up the lifts to level 18 to my usual desk in the Brisbane Integrated Operations Centre. At Rio we hot desk throughout the building except on this floor which I am grateful for considering the set-up I’ve been given!

Rio Tinto - Male graduate sitting on his desk

7.15 AM

After I put my lunch and snacks away and organise my desk I’ll briefly scroll through my emails, check my calendar and update my diary before the stand-up meeting with my team’s members overviewing the operations yesterday, a brief schedule of today and a bit of general banter 

8.00 AM

The first formal and back-to-back meeting of the day. This video conference between the operations centre (OC) and site manager’s agenda is discussing what is happening on the ground. This can include information about maintenance shutdowns, production targets and how compact is the shipping line-up. 

8.30 AM
 
The exact same meeting, just for the second mine site region that the OC schedules. 

9.15 AM
  
I’d be lying if I said I wasn’t a bit of a coffee snob. I use this time of the day to get out of the office with my colleagues and walk down to the local (Strauss), an alleyway/Melbourne inspired café. What started as being a general coffee run is now and essential part of our schedule where we, the data scientist, can debrief our current workload, discuss errors and pitch new ideas to our current longer-term projects that weren’t discussed in the earlier meetings.

9.45 AM
 
After spending most of the morning socialising (more common than not) it’s time to sit down and grind out the ad-hoc tasks I had been assigned throughout the morning’s meetings. These tasks can vary from ETL data processes from our on-site historian SQL systems through to a quick analysis. This morning’s task; comparing the current ship loader rates against historical information and identifying if there are any underlying trends or relationships in data. 

11.00 AM
 
At Rio Tinto as a graduate you are assigned with a senior mentor outside of you team to catch-up with on a regular basis to build upon your technical and professional skillset. This meeting, with my mentor, was quick discussion on what cloud platforms are approved and utilised internally and suggestions productising my current project!

12.00 PM
 
Third “formal” meeting of the day, the data strategy catch-up. 

Rio Tinto is internally pushing teams to operate in an industry 4.0 approach. This time is utilised to identify pain points in our current data workflow and reports how we might improve upon and make a more intuitive process. 

At this stage, we are flagging all manual tasks that can developed into a more automated approach, most likely a Power BI solution, for more data-driven decisions (aka the death of spreadsheets!).

1.00 PM
 
After continuing the ad-hoc tasks I had been assigned earlier in the day it’s lunch time. I try to meal-prep on a Sunday afternoon so I don’t “forget” my lunch, but on the days that I do there’s always somewhere new to eat in the Wintergarden with the team that is always capped off with a bubble tea. 

2.00 PM
 
Mid-Afternoon is where I spend the majority of the time on project work, however not before a second coffee! Up on level 21 (I try to walk the stairs for exercise) we have an industrial Nespresso machine, that is a close second to the Strauss, that you can brew while taking in the view of Brisbane City. 

2.05 PM

With a hot coffee in hand it’s time to work on my long-term project’s. Using the discussions from the early morning coffee and the catch-up with my mentor I’m booting up my either my AWS environment or R-Server and begin coding! (Unless it’s a research day where most of the time is spent reading academic papers and understanding what machine learning techniques can be applied). On a stressful day, I find it’s always important to block out time (including closing you emails) to get ahead on work that’s deadlines are quickly approaching. 

4.00 PM
 
A quick debrief halfway out the door with my manager on what today consisted of, any feedback, and if there are any out-of-schedule meetings I should expect tomorrow morning. 

4.30 PM
 
A massive benefit to my role is the flexible work hours that allow myself to have schedule that best suits my lifestyle. Living close to the city I am fortunate enough to have a gym within the apartment complex, a commercial gym and F45 all within a 250m radius of each other. Today I am quickly ducking to my apartment, drop my bags off and get changed for an intense F45 cardio class!

6.00 PM
 
After taking an extra 30 minutes to regain my breath and shower it’s time to start preparing dinner while watching Bondi Rescue (Yes they still play it you just need to know the right channel). I was a little unprepared tonight so I’m throwing together the majority of leftover vegetables into a stir-fry.  

7.00 PM
 
After sitting down and watching a combination of the news and MAFS, I have built up the last of my daily motivation to start a new course on DataCamp titled Supply Chain Analytics in Python. A massive benefit for working at Rio Tinto is the learning budget to develop your skill set and achieve your professional development plan.
 
I am a massive advocate for continuous learning, and although I am no longer at university I am leveraging these online courses to ensure I am constantly improving technically!

9.00 PM
 
It’s time for bed, although I’ll probably be on my phone scrolling Instagram and watching YouTube videos for the next hour before I actually fall asleep. 

I’ll give a last check of my work phone to see if anything important has landed in my inbox before I call it a night knowing that I’ll be snoozing my alarm again in the morning.