From stacks of study and a summer internship to a graduate gig at CBA, machine learning engineer Genevieve Richards has made the most of her career opportunities
Genevieve Richards has studied a lot. And not just STEM-related courses typical of her engineering role. Now working as a grad at the Commonwealth Bank of Australia (CBA), she kicked off her tertiary studies with a Bachelor of Arts (Psychology and Linguistics) at The University of Queensland, where working on a computational linguistics project sparked her initial interest in tech.
“It gave me a range of soft skills and a huge understanding of people,” she says of the course. “I learnt how to learn, analyse and pick up concepts quickly which I now continue to do at work.”
Seeking out further training that was a little more specialised and hands-on, Genevieve followed up her first three years of study with an IT degree at QUT. Becoming fluent – and bilingual – in code, along with a bunch of other complex IT systems, equipped her with the skills and confidence to apply for work experience at text analytics start-up Kapiche, and later an internship at the CBA.
“I came across the CBA internship while searching for something to do over the summer before my final year,” says Genevieve, who was blown away by the sheer number of different tech opportunities within the bank. “I ended up loving it so much that I applied for the graduate program straight away.”
Genevieve went through the official interview process, which included psychometric testing and a half-day assessment session. Two days later she found out she’d been selected, and after wrapping up her studies, she joined CBA’s Analytics and Information department as a full time machine learning engineer.
So, what does a machine learning engineer do?
Genevieve has been a permanent member of the CBA grad team for seven months now, and works across several of the bank’s offices within the Sydney city. Apart from the fun fact that there are ping pong and foosball tables in the office – one of the coolest things about her gig is the variety of projects that she gets to work on.
At the moment, Genevieve is working on a project that aims to predict the number of incidents an IT service might receive by using lots of different data points. The Machine Learning models will then take the data and put it all together to come up with an equation that we use to make the predictions. It’s kind of like using data to predict the future.
“Most days involve writing code, but there are also meetings with different stakeholders and subject matter experts,” she explains. “I’ve been spending a lot of time on design lately too.”
And you can forget the geeky, male-dominated IT department stereotype. “There are a lot more women taking on technical roles,” says Genevieve. “There are four incredibly talented female data engineers in our team!”
When Genevieve isn’t writing code or playing ping-pong in the office, you can find her walking around Sydney – “it’s a great way to explore new places!” – or learning to ski – “I’m heading over to Canada in February!”.
And her advice to young grads wanting to get into a similar field? “Put yourself out there! Send an email to a company you’re interested in!.”
Genevieve’s career and study pathway:
>> Bachelor of Arts, The University of Queensland
>> Bachelor of Information Technology, QUT
>> Summer Intern, CBA
>> Graduate Machine Learning Engineer, CBA
This article was brought to you in partnership with the Commonwealth Bank of Australia.
Author: Cassie Steel
As Refraction’s digital editor, Cassie Steel spends her days researching robots and stalking famous scientists on Twitter.