I had the pleasure of talking with Full Stack Modeller's Giles Male this week about what employers are looking for in Data Analysis and Financial Modelling candidates.
We went pretty deep into the state of the job market, remote working, the technical and non-technical skills employers want to see, how they assess candidates, and even got into some details about our respective training offerings.
Plus, we recorded the whole thing for you. Check it below.
If you're considering a career in Data or in Financial Modelling, trying to find a new job, or just trying to do some career planning, this one should help you out.
And if you are interested in either the Full Stack or Maven Analytics training options, there is still time to enroll in either program...
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John Pauler
Partner & CRO
John brings over 15 years of business intelligence experience to the Maven team, having worked with companies ranging from Fortune 500 to early-stage startups. As a MySQL expert, he has played leadership roles across analytics, marketing, SaaS and product teams.
Frequently Asked Questions
What is Maven Analytics?
Maven Analytics is an online learning platform that helps professionals and organizations build practical data and AI skills in analytics, business intelligence, and data science. Our hands-on courses are designed to help learners stay competitive and future-proof their careers in the age of AI.
Are data analysis and data science still good career paths?
Absolutely. As long as companies collect and use data, they need people who know how to turn that data into results. Roles are changing, and so are the skills needed to succeed, but the career paths remain strong. Focus on data literacy fundamentals, business thinking, communication skills, and learning how to use modern data and AI tools, and you can build a strong career.
Will AI replace data jobs?
AI is changing how data professionals work, but it is not replacing the need for skilled analysts and data scientists. Instead, AI is becoming another tool in the data workflow. Organizations still need people who can ask the right questions, interpret results, communicate insights, and apply data to real business decisions. The most successful professionals will be those who learn how to combine core data skills with modern AI tools.
How can I future-proof my career in analytics?
Future-proofing your analytics career means building strong core data skills, understanding business context, and learning how to work effectively with AI rather than compete with it. The goal is to become a better analyst, problem solver, and decision-maker.
How long does it take to build job-ready data skills?
That depends on your starting point and goals, but many learners can build meaningful skills over a few months with consistent practice, even when studying part-time. The most important factor is applying what you learn through hands-on projects and real business problems.
