It’s no surprise that career opportunities within the business intelligence, data, and AI sectors have grown massively in recent years.
Data is everywhere, so data analytics is critical in helping businesses improve all types of decision outcomes.
Technology is constantly unearthing new ways to be innovative and efficient, making it an equally exciting and challenging area to work within.
On 14 March 2023, we were joined by three speakers who shared their experiences of internship, leadership, and entrepreneurship within these evolving areas of the technological industry, and how students from a range of academic backgrounds can go into them.
Our speakers were:
Teik Keat Tee
Finance Business Intelligence Intern
Sam Haynes
Head of Risk Analytics
Helen Tanner
Director at Data Cubed
Here are our top 7 takeaways from the event:
Go above and beyond: From a recruiter’s point of view, there is so much competition for roles that you need to try and stand out during the application process. As well as providing a tailored CV and cover letter, Helen mentioned being impressed by applicants who do more than they are asked and complete an additional task (whether it be as small as a data dashboard) alongside their required interview task. These extras can help get you through that initial application sift.
Research-specific requirements: When applying for junior roles, bear in mind that they don’t always include details of the software that the company uses. Taking a look at senior roles within the organisation can help you form an idea of which software they do use. Likewise, when researching individuals ahead of you in their careers, LinkedIn can be a great resource to discover exactly what they did to get there.
Quality over quantity: If you are concerned about how to balance your career development with academic excellence, then small but relevant projects can give you a great chance to talk about your experience.
You can base your projects on areas that already interest you and even hobbies, as this will make it easier to maintain your enthusiasm for them.
As an Economics and Finance student, Teik didn’t originally have a technology interest but was still able to pull out relevant knowledge from his degree in areas like Econometrics.
Find your way in: Don’t be disheartened if you aren’t studying for a technology-related degree. Business analysis (prior to data collection) requires a logical mind so this can be a way to break into a data science background. For instance, a knowledge of law can be really useful with technical project management.
To help you evolve into your speciality, Power BI has lots of free training opportunities. If you lean towards coding, aim to become confident with using SEQUEL and Python as they are the main coding languages used. There will always need to be a data element to your work but once you’re in a company, you have more freedom to decide which specific route you’d like to pursue.
‘AI won’t replace your job, someone using AI will’
Helen Tanner
The vast majority of businesses do not use AI so early adopters tend to be the most technically ambitious and high growth. This already huge market will only continue to grow so organisations will have to scale themselves to reflect this. However, don’t forget that you are still working for people. You need to be able to explain to your clients exactly how you have reached a conclusion through the AI data so communication skills are important.
Deciding between start-ups or corporate: There are pros and cons to both so it may depend on your personality type. Start-ups are extremely high exposure so ambitious individuals are more likely to progress rapidly through a small team. This may also mean, however, that you have fewer opportunities than you would do in a corporate business to learn from those around you.
Corporate businesses usually offer a fixed and more narrow progression plan, as well as funding for additional qualifications. You will have more support, but consequently more rules. Sam used his experience in a smaller company to move into a larger organisation, demonstrating the skills they were in need of.
Should you do a Masters? There seems to be no clear answer to this question. Further study may be the most efficient way to progress into one of the larger tech companies but it is a large expense.
Volunteering work and getting hands-on experience with practical data may be a far more accessible way to build a portfolio. You may need additional qualifications down the line, but first, prioritise making sure that you actually enjoy and have an interest in the work before committing yourself to a postgraduate course.
Would you like to know more?
For those of you interested in learning more about tech founder groups and particularly organisations in Bristol, Helen recommended SETsquared and NatWest Accelerator as great starting points!
We would also like to suggest you take a look at the Careers Service’s technology sector guide on ‘Data, Analytics and AI’ for additional resources. Also, our flagship spring careers fair: ‘Get Hired’, is taking place on 3 May 2023 and is a unique opportunity to begin networking with prospective employers.
Blog written by Ella Woszczyk, a second-year English student and Career Peer Support Assistant.