If you’re applying for junior roles right now, you’ve probably noticed something weird: the listings still exist, but the doors just feel heavier to push. Applications go into a void and you see friends with decent CVs getting ghosted.
You’re not imagining it. I’ve covered this in the blog before, when I went through Anthropic’s report on AI’s labor market impact: junior-level roles in AI-exposed occupations are showing a real, statistically significant drop in entry rates for workers aged 22–25. People aren’t getting too laid off (although we have layoffs from big techs, the unemployment rate hasn’t moved significantly), they’re just not getting hired in the first place.
During the past year, I’ve interviewed more than 500 candidates for DareData, but also recommended dozens of candidates for companies that reach out to me asking for Data Scientists, ML Engineers and Product Managers. In this blog post, I want to share what’s actually working for the people who break through. None of this is “hustle harder” advice and it’s not technical, for sure. And a lot of what hiring managers care about isn’t on the list of things candidates think they should be optimising for — nor in the job post.
Let’s get into it.
1. Be the person who takes care of things
This is, by some distance, the most underrated skill in the modern job market. It’s also the one I look for first when I’m interviewing someone for a junior role — especially looking for situations where they’ve assumed responsibility when they didn’t need to. I’ve spoken about this skill over and over on my leadership blog.
“Taking care of things” sounds vague, but it’s simple: when something is on your plate, everyone knows that you will find the resources to get it done (note that this doesn’t mean that you have the resource, but that you will find the resources needed to complete a task).
If you’ve ever worked in a team, you know exactly the kind of person I mean, and you also know how rare they are.
The reason this skill is so valuable now is because AI handles the task layer fairly well. What it can’t do is own a thread of work end-to-end across humans, systems, and ambiguity. That’s the gap that’s getting more valuable and if you become known for closing loops, you become hireable in a way that doesn’t depend on which framework is hot this year.
You can practise this skill anywhere: at school, in volunteer work, even at home. Take on the task that looks too big and just ace it through.
2. Learn to disagree without being a pain
The cliché version of teamwork advice is “be a team player,” which is too vague. The thing I actually screen for in interviews is whether someone can disagree with me constructively in a 45-minute conversation.
I’ll float an opinion that’s deliberately a bit off, about an architectural choice, or a process question, or how to scope a project. I want to see how the candidates think and if they can trade ideas and opinions without becoming defensive. The bad responses are the obvious ones (just agreeing with me, or arguing aggressively).
Disagreeing well is a skill that compounds with experience, but you can get a head start just by watching how badly most young people do it. 🙂
3. Volunteer somewhere
Volunteering is the holy grail of networking.
My first proper gig with DareData came through a volunteer organisation. I wasn’t applying for jobs at that point, I was just helping run things at a non-profit context where I happened to meet people who later thought of me when a leadership position opened up. Volunteering in spaces tied to the work you want to do is how you expose yourself to luck.
The mistake juniors make is treating volunteer work as a CV line. The CV line is the byproduct, while the actual value is that you spend time around people who do things, and those people remember you. Six months later when somebody says “we need someone for X”, your name is on top of the list, especially if you follow advice number 1.
If you’re early career, find a student club, an NGO, an open-source project, a meetup group. To be useful in a place where useful people are paying attention.
4. Your portfolio is your resume now
If you’re a technical person, GitHub matters and a personal website matters. Anything that lets a hiring manager see your work matters in a world flooded by AI generated CVs.
When I’m reviewing a junior application, the CV tells me what you claim but the portfolio tells me what’s actually true. As I mostly hire AI engineers, I can tell within 30 seconds of looking at someone’s GitHub whether they understand what they’re doing, the commit messages, the README quality, the structure of the projects, whether the repos are abandoned shells or actual working things. Yes, and I can spot AI generated slop in repos too!
You don’t need impressive projects, you just need real projects tied with something you enjoy and love. The size doesn’t matter, but how much passion you put in it, does.
If you’re not technical: the same logic applies, just in a different format. A portfolio site with case studies, a few well-written analyses on Medium, A presentation deck from a real project you ran. Anything that lets someone evaluate the work, not just the claim.
5. Write in public
Most young people think they don’t have anything worth saying until they’re more experienced and that’s wrong. I’ve read pieces from students so full of curiosity that I’d happily read a long-form essay from them.
Pick a topic you care about and start writing about it publicly. Substack, Medium, LinkedIn, your own blog, it doesn’t matter. The platform matters less than the consistency. The reason this works is simple: most juniors are invisible to hiring managers until they apply. If you write publicly about your field for six months, you arrive at the interview already half-known. The hiring manager may have read your stuff or noted you.
The trick is to write about what you’re learning, not what you’ve mastered. It’s a win-win: you may get noticed, but also improve on the compreheension of topics you want to know about.
Oh, and never let AI define your writing style. 🙂 Everyone can spot obvious AI prose from a mile away now, don’t cut that corner.
6. Get fluent at working with AI before AI works without you
This is probably the most obvious advice.
Every junior I interview now, I quietly assess for one thing: can they work with an AI tool intelligently? Today, working with AI intelligently is not copy-pasting code or paragraphs from AI tools. I mean more: do they know when to trust the output, when to push back, when to verify, when to throw it out? Do they treat the model like a teammate they’re supervising, or like an oracle?
The juniors who are getting hired right now treat AI as a multiplier on their judgement. The ones who aren’t, treat it as a substitute for their judgement.
Do real work with these tools, frequently, and pay attention to where they help you and where they hurt you.
If you’re a student or a recent grad reading this, I don’t want to fool you: the market is harder than it was, and the anxiety you’re feeling is rational. Pretending otherwise would be wrong.
But the things that get you hired right now are not the things AI is automating. AI is good at tasks, but it’s not good at owning a thread of work across humans and ambiguity, at disagreeing constructively in a room full of opinions, at noticing what nobody assigned, at being the person colleagues trust. That’s still you.
Humans aren’t task executors. We’re the layer that maps how tasks connect, who needs what, when something is going off the rails, and what’s actually worth doing in the first place. That layer is getting more valuable, because there’s more output flying around that needs someone with judgement to make sense of it.
Show up as the kind of candidate who already looks like they’re doing the job, and the door opens. When you establish yourself as a reliable future professional, your reputation does the networking for you, no applications required.