As a Recruiter who reviews countless AI and data science CVs each week, I've seen it all, from “AI visionary” to “machine learning ninja.
”The truth? Buzzwords alone won’t get you shortlisted.
If you want to stand out and truly connect with hiring managers, here’s what I recommend:
Show your impact with numbers
Rather than simply saying “improved model performance”... quantify it:
“Improved churn prediction model accuracy by 12%, reducing customer attrition by 8%.”
Numbers build credibility and immediately signal real-world value.
Highlight production experience
Many applicants focus on experimental work or theoretical knowledge. If you’ve deployed models or AI systems into production, emphasise it.
Mention the scale, user impact, and any challenges you overcame… this is gold to hiring teams.
Connect your work to business outcomes
AI and data professionals aren’t just technical, they solve business problems.
Show how your work contributed to better decision-making, increased revenue, cost savings, or improved user experience.
Show collaboration and communication skills
Employers want people who can partner with product teams, engineers, and non-technical stakeholders.
Share examples where you translated complex findings into actionable insights or influenced strategic decisions.
Don’t hide behind jargon
A CV full of big buzzwords with no substance is a red flag.
Be clear and concrete about what you actually did, explain how you used the tools, the methods, and, most importantly, the results.
My advice:
Treat your CV like your personal data story. Focus on clarity, impact, and outcomes, not just technical depth.
This approach not only gets you noticed but also sets the tone for a strong interview conversation.
So, if you’re updating your CV now, take a step back and ask:
Would someone outside my immediate circle understand and appreciate the impact I made?
