As I conclude my 7th year of teaching at Northeastern University (that makes me feel old), the age old question from students is, "what can I do to help me get a job?"
Over this time, the answer has really evolved especially in the AI / Data / Analytics space, but here are the 2 things going into 2026 that I recommend - as someone who is both a professor and someone that interviews and hires.
1. Critical Thinking > Coding
In this post-Stack Overflow to AI world, coding and programming is not a differentiator anymore.
Being able to logically tell me how you would solve a problem is way more effective. In the last 2 years, I have not given a coding test, but more logic questions to see if you can ask the right questions and work toward a solution.
How to practice this? Use AI to give you some brain teasers and work with ChatGPT or Claude to see if you can solve it with them. The skill isn't writing the code - it's breaking down the problem.
2. Content > Kaggle Datasets
Every resume in the data science space is on 1 of 10 datasets, it feels like.
Not saying you need to be a TikTok star, but turn your project into a video. AI has made that easy with Microsoft Clipchamp and Google Vids.
In my professional career, this has been a huge win over the last year and has driven engagement and marketing on the products I work on.
I'd rather look at your content portfolio - how you present and showcase your work - than hearing about how you solved real estate pricing in King's County.
Hopefully this is helpful for new grads or people looking to pivot in their careers in this competitive space!
Have questions about breaking into AI/Data? Reach out - always happy to help.
