In less than 5 months, Dominic Thomson was able to successfully up-skill with practical Data Science and AI training and land his dream role at PwC! Throughout the Institute of Data’s Data Science and AI Full-time program at the University of Technology Sydney, Dominic received technical, interpersonal and career skills training, transforming his future career prospects.
Coming from a more technical data background himself, Dominic recognised the need to up-skill and stay relevant in the job market as Artificial Intelligence and Data Science continues to disrupt many industries across the world. Have a read through his journey below:
Dominic, tell us more about your career background! What motivated you to upskill / pursue a career in Data Science and AI?
“My career background is around the data analytics profession within the sports industry. But I really wanted to develop a skillset that is more equipped to handling predictive analytics especially in the realm of data science!”
How many years of industry experience did you have prior to joining the full-time program?
“I had around 18 months experience prior to joining the full-time program.”
What was the most challenging aspect of completing the course and what did you enjoy the most?
“The most challenging aspect was the initial technical learning curve, especially around Python. I really enjoyed learning the almost infinite multitude of ways we can wrangle and interrogate data. In particular, I enjoyed learning to constantly vary my approach and use different models to identify key factors & predictors.”
What were your career goals before upskilling to data? How has your outlook changed?
“My previous career goals were seemingly stagnant and not high enough. The course was very inspiring and motivational in the way it pushed me to achieve and succeed more in my career.”
Why did you choose to join the Full-Time Program in particular? What appealed to you?
“The full-time program was more aligned with my other commitments as I was unavailable to study weekends. The consistent interactions and classes were also important to my learning.”
You’re now working with PwC – Congratulations! How did you get a job in the industry after completing your training and what guidance would you give someone applying for jobs after upskilling?
“I would highly suggest trying to draw links between your studies and the job position. Focus on communicating how the skills you’ve learned can directly play a role in your job. You will be surprised at the amount of cross-over between the course and job opportunities – which on face value may not appear to be directly data science related.”
Would you recommend upskilling to fellow professionals?
“Yes, definitely. Data science is evolving rapidly and becoming pervasive across almost all industries. Soon, everyone will have to be prepared to handle data.”
How did you determine the focus of your final Capstone project during the course? What did it teach you and how did you find the process?
“I wanted to wrestle with a current problem, ideally in Australia. Similarly, I needed an appropriate dataset that was readily available. Hence I landed on the impact of COVID on the lodging market using public Airbnb data.
I learnt that we need to be open and flexible towards how we wrangle the data. There is no one set method that will give you the answer you are looking for. Being circumspect and using a variety of methods and models is key to understanding the data.”
Now that you’re trained with in-demand skills and working in the industry, what’s your future career plan?
“The data science industry is constantly evolving. An integral part of being successful in this profession is ensuring we are continually growing and learning. Experimenting with new models and methods is critical and doesn’t allow our mindsets to become outdated and inevitably obsolete.”
Congratulations on your major career success Dominic!
If you are interested in up-skilling and landing a job position within the Data Science field, book in a consultation with our Data Career Consultants today.