Puzzle Pieces: AI, Analytics and the First Real Job

Too many data professionals are letting AI do their thinking. The result is broken pipelines, misaligned projects, and careers that stall at the first real challenge. Learning to use AI as a data analyst effectively, without surrendering the strategic judgement that makes the output valuable, is the capability that separates analysts who advance from those who plateau.

In the first conversation of this series, we look at where AI genuinely accelerates analytics work, where it quietly leads you down the wrong methodological path and why adaptability is the most important attribute any new analytics graduate can develop.

Host Eduardo Ariño de la Rubia is joined by Seneca Miller, a Data Analytics Scientist at eMedia Monitor in Vienna. She is a 2025 graduate of CEU’s Master of Science in Business Analytics programme and winner of the cohort’s Best Capstone Award.

THINGS WE SPOKE ABOUT

- Transitioning from marketing into analytics as a working professional

- Being a company’s first data hire with full project ownership

- How AI accelerated growth while creating knowledge blind spots

- When to step back from AI and rely on your own judgement

- What the MSBA should teach more and less of in the future

GUEST DETAILS

Seneca Miller is a Data Analytics Scientist at eMedia Monitor, a media monitoring company based in Vienna. A 2025 graduate of CEU’s Master of Science in Business Analytics programme, she won the cohort’s Best Capstone Award and joined eMedia Monitor as their first dedicated analytics hire. Reporting directly to the CEO, she designs and delivers data projects from the ground up, from NLP pipelines to topic classification models.

QUOTES

- “I can look at my project and say this from start to finish was what I did.” - Seneca Miller

- “People will outsource their thinking to AI. And that’s where people get in trouble.” - Seneca Miller

- “You might have linear growth, but this transforms everything to exponential growth.” - Seneca Miller

- “If I didn’t have this course, I would just have a bunch of puzzle pieces still sitting there that I’d still be trying to put together myself.” - Seneca Miller

- “It’s not the technical aspect of the work anymore that if you can write code, if you can put together a pipeline, it’s do you understand the business needs the business context, what that business wants, because every business incentivizes different things.” - Seneca Miller

KEYWORDS

#DataAnalytics #AnalyticsCareer #AITools #DataScience #MsbaProgram