A lot of people come to me after running their resume through AI or asking a non-specialist friend to clean it up. The problem? They end up with a resume full of gaps and missed opportunities. Here's what I actually look for when I review marketing and data resumes.
Start with the basics in your header section. If you don't need sponsorship, say so — that's a green flag for a lot of hiring managers. If you're open to relocating, note it. Include your LinkedIn and, if you're in data, your GitHub. Small details that make a recruiter's job easier.
When listing your companies, add a few words of context next to each name — industry, stage, size. If the company is small and has LLC in the name, consider dropping the LLC. When describing your work, avoid technical jargon that an HR generalist won't understand. "Identify risk" means nothing to a non-analyst. "Identify opportunities for cost optimization" is much clearer.
Keep the whole thing to one page. Font size should stay at 10.5 or above. Leave breathing room between sections and positions — a recruiter scanning hundreds of resumes in a day will skip dense, hard-to-read formatting. Each bullet should be no longer than three lines.
Don't lie about tools or inflate your numbers. If you put a metric on your resume, expect to be asked exactly how you calculated it. Data-driven hiring managers will probe. The same goes for tools — if you've never used it, don't list it.
If you're in multi-channel marketing, use your first bullet to summarize the channels you own (social, email, paid media, SEO, etc.), then dedicate separate bullets to each with specifics. If you only managed social media, don't write "multi-channel" — that will catch up with you in the interview. And for data analysts: building a dashboard that saved reporting time is not impressive on its own. The real win is showing that your insights drove a business decision that saved money or grew revenue.
© 2026 Rachel Hong · Accelerator Consulting