Tomos is on his final placement on the Welsh Data Science Graduate Programme. Here he shares his what attracted him to the programme, his career highlights and some tips if you’re considering applying.
What attracted you the Welsh Data Science Graduate Programme?
When I read about the unique ability to rotate between companies the attraction was immediate. I was initially looking for an opportunity that would let me exercise and expand my skills with applied statistics. There was little scope to improve these skills within the workplace, and a full-time MSc. would not allow me to apply new skills. The programme gave me the opportunity to balance both whilst earning an income at the same time.
What surprised you the most about the Programme?
Despite being a grad, I found myself in positions that required me to continuously improve the value that is derived from the organisation’s data. This level of responsibility, to do what’s right and help others, was an instant motivational boost.
Had you always wanted a career in Data Science?
I love telling stories with data and using visualisations to help bring that data to life. I wanted a job where I could do this. I knew that as a data scientist I could turn seemingly meaningless data into facts.
Where are you working now?
I’m currently on my final rotation of the programme and am working at Amber Energy as a Data Scientist.
Do you think you’d be working for the company/role had you not taken part in the programme?
Not at all. The Data Science Programme works with a range of companies across different sectors such as financial services and utilities. I have previous experience working in utilities but never thought I’d work in finance. An 8-month placement was a great introduction to the financial services sector.
Furthermore, data science roles are hard to get into as there is no unified definition of the field. More and more businesses have a data science team now but they’re either hard to find or difficult to get into. However, this programme balances that by allowing you to experience different data science set-ups in different industries.
How have you balanced your full- time work and studying for the MSc?
I’ve learnt to follow a few principles which have helped me to balance full-time work and studying for the MSc; It is important to organise and prioritise work well in advance. Understand that university works on deadlines whilst your job is more day-to-day.
Be honest with your line manager and/or boss. They understand that you’re completing a Master’s and will take this into account.Avoid burnout.
Do you feel the employers treated you as an employee or as a graduate?
Both. In my day to day job I am given the respect and same treatment as any other employee but, when the employers also recognise that as a graduate you are required to attend university and courses. The employers I have worked with on the programme all considered the MSc as ‘innovation time’ because data science methods are continuously changing. Therefore, spending time learning about the latest trends and methods is a good thing.
Can you share one of your career highlights since you embarked on the programme?
During my first rotation, as a junior data scientist, I was part of a team that helped reduce complaints and alleviate customer pain-points. Through rigorous problem solving and communication with the right people we were able to create information that influenced decision-making. The findings indirectly changed a company policy within weeks and was predicted to save the business a six-figure sum in the first year of implementation. I was really proud to be part of this project and it spurred me on in my critical thinking.
What advice would you give to graduates who are thinking about applying to the programme?
For your application and interview, demonstrate experience and competencies that are outside the core remit of data science. Make sure to underline skills and experience such as teamwork, communication, and business acumen. Being able to translate data science products will require these skills.
Thanks to Tomos for sharing his insights!