I completed the Machine Learning Engineering stream, despite having no prior experience in this area.
Prior to joining Kubrick in September of 2020, I was completing my degree at the University of Leeds where I studied Theoretical Physics. In my final year, I focused on quantum physics, specifically quantum algorithms for my final master’s project. I was also lucky enough to be able to spend one of my years at university studying abroad in America. I attended Stony Brook University in New York State and it was an amazing experience both academically and personally.
I was compelled to pursue a career in data as I believe it is a massively underused resource which can play a part in solving so many issues we currently face as a society. Data has applications across countless industries, but I have always been particularly interested in the medical and pharmaceutical impacts of data. There are so many examples of the way medical data is being used daily to improve patients experience from diagnostic tools to better ways to track side effects of medications. I chose to pursue a career in data so I could be a part of these innovations and make my own contributions.
I found out about Kubrick in my final year at university and was drawn to apply due to the invaluable opportunity to keep learning after graduation and gain the skills I would need to be a data professional. After further research I was excited to apply, having seen the importance Kubrick place on diversity and their commitment to addressing the current under-representation of women in data.
The training at Kubrick was a fast-paced, but a great insight into data and the technical foundations required when working in this area. I completed the Machine Learning Engineering stream, despite having no prior experience in this area, and it was great to have all the concepts clearly explained and demonstrated and it’s given me a very solid foundation to build on further.
The culture at Kubrick is very supportive with trainers always willing to spend some extra time with you if you’re struggling. The people team is also very supportive. I would say one of the biggest bonuses of the Kubrick model is the large network you have available to ask for help during and beyond your training. Within your cohort there are 25 or so other people all starting their careers at the same time who are likely to be facing or have faced the same issues as you. This combined with the wider network of Kubrick consultants outside your cohort, who are always happy to offer advice and support, is a great way to start your career.
Out of the multiple projects we completed throughout training, the one I am most proud of was based around predicting customer churn. We were given a large database of transactions for a savings account; alongside this, we had a database of information about each customer. We were asked to use these two databases to predict, given the customers previous transactions, the likelihood that the customer would leave the bank in the next month. I particularly enjoyed this project as we had a lot of autonomy with how we decided to approach the problem and what methods we thought were most appropriate.