Maths is a major part of entering the field of data science but there’s a lot more to it than that.
When it comes to data science, there is a world of possibilities for those who want to enter the industry.
Those with mathematical skills and numerical backgrounds will already be in good shape to take on a successful data science career, but there’s a lot more to it than that.
Martin McGovern is an actuary and data scientist in the Aon Centre for Innovation and Analytics (ACIA). With a numerical and research-focused background, McGovern is a fully qualified actuary with a PhD in theoretical physics.
“I became interested in data science as it is the ideal mix between technology, mathematics and statistics, and provides a chance to research new ideas and be part of real innovation in industry,” he said.
Despite maths being a major part of his career as a data scientist, McGovern said it was quite challenging moving from an actuarial background to a role that required programming knowledge.
“I did use Fortran programming during my PhD but had not previously used Python. I have upskilled by doing a programming course focused on Python for machine learning, and the support I have received from my colleagues has helped me improve my skills,” he said. “Another real impact to my career to date is the hands-on learning experience I receive from ACIA as well as my colleagues.”
McGovern also said that moving from a research-focused PhD into the commercial job sector is the hardest thing he has faced in his career so far. “However, I feel that I have gained so much knowledge in different fields; it has helped me give a different perspective and add value to the various roles I have been in to date,” he said.
“My latest move has been internal within Aon, moving from my actuarial role to the data science team in ACIA. The work culture here is similar to my previous Aon role, which has made the move really enjoyable.”
It isn’t just the technical skills that are important in data science. McGovern said that his determination is a major personality trait that makes him suited to his job as a data scientist.
“I like to really understand the underlying theory and background of projects I am working on, so I always research before I start. I feel that this helps me get a better understanding of the project and how it works.”
The STEM community
Keeping in touch with the STEM community is a great way to learn about what’s going on in the industry as well as making valuable connections.
McGovern said that he attends data scientist meet-ups regularly for this very reason. “I have also joined the Analytics Institute, the professional membership body for the data science and analytics industry, and they organise several events around new and exciting areas in data science.”
However, he does wish that more women would be encouraged into joining the STEM industry. “I feel that at ACIA we have a diverse workforce, which is great. We recently had Teen-Turn in, which is an organisation that helps young women to be exposed to STEM careers at an early age. I honestly think that is a great initiative!”
McGovern also said that mentorship is important and, speaking personally, it played a huge role in his own career. “I feel that everyone should be mentored in their career as it acts as a support system and guidance for you as an individual; you learn from expertise in your field. It’s hard to gain all that from a book, and the combination of mentoring with hands-on experience gives you the best results.”
Entering the data science industry
For anyone interested in beginning a data science career, it’s a very exciting time. McGovern said the best thing about working in the industry is the new technologies that are already in development.
“At ACIA, I am exposed to a variety of technologies and tools on a day-to-day basis, which helps me improve my skills and enables me to carry out my work efficiently and effectively.”
He said he would advise anyone thinking about a data science career to be open-minded to challenges they may face, willing to learn and ready to adapt to different technologies.
“If you enjoy coding, mathematics and research, you should look into a career in data science, as the opportunities are endless!”