Your resume is no longer enough in this data analyst job market.

31 Oct 2025 · 1 min

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1:02

In this concise, high‑energy talk, Kedeisha Bryan argues that LinkedIn has effectively replaced traditional applicant tracking systems (ATS) for data analyst recruitment, citing that 87% of recruiters vet candidates on the platform before reviewing a resume. She explains why a LinkedIn profile must be treated as a personal brand rather than a static online résumé. Bryan walks through the five critical elements of a data‑analyst‑focused LinkedIn profile: a results‑oriented headline that conveys analytical impact, a visually striking banner that reinforces the brand, a narrative‑driven summary that tells why the analyst works with data, a curated features section that highlights portfolio projects, case studies, and measurable wins, and the overall need to make the profile “scream” problem‑solving ability. The talk is instructional and persuasive, urging analysts to shift from generic buzzwords to concrete, outcome‑focused language to capture recruiter attention.

Chapters

LinkedIn is the new ATS. Here's what will blow your mind. 87% of recruiters use LinkedIn to vet candidates before they even look at your resume. That means your LinkedIn profile is not optional anymore. This is your first impression. It's your digital storefront, and this is where recruiters will decide if you're even worth their time. But here's what most people get wrong. They treat LinkedIn like a boring online resume. They list their job titles, throw in some buzzwords, and call it a day. That's not a brand. That is just white noise. Your LinkedIn needs to scream, I am an analyst, I solve problems, and I deliver results. Your headline can't just say aspiring data analyst. That's weak and that's forgettable. It needs to say something like helping business turn data into decisions, SQL, Tableau, Python, or data analyst transforming messy data into actionable insights. Your banner, use it. Don't just leave it blank. Add a visual that reinforces your brand. Your summary, tell your story. Why data? What problems do you solve and what makes you different? In your features section, make sure you showcase your portfolio projects, case studies, and your wins.