Skip Machine Learning. Do This Instead

15 Jul 2026 · 1 min

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1:29

In this career‑advice video, Kedeisha Bryan argues that aspiring data professionals should bypass the common focus on machine learning and instead launch their careers as data analysts. She contends that the entry barrier for analyst roles is far lower—requiring only SQL, Excel, and the ability to narrate data—while still offering six‑figure salaries ($70k‑$85k) right out of the gate. Bryan emphasizes that analyst positions provide real business experience, stakeholder relationships, and a deep understanding of how data drives decisions, which later accelerates promotions and salary growth when transitioning to data science or machine learning roles. She claims analysts often see faster salary bumps than traditional college graduates because they have already demonstrated value. The video concludes with a call‑to‑action, inviting viewers to comment “data” to receive a free roadmap for breaking into the field.

Chapters

The fastest way to break into a 6-figure data career is not machine learning, but it's starting as a data analyst first. Everyone thinks they need to learn Python, build neural networks, and master all these algorithms before they can get hired. That is wrong. That's actually the hardest path, not the smartest one. Here is what's actually working right now. Start as a data analyst. The barrier to entry is way lower than a data scientist. You don't need a computer science degree. You don't need to spend 2 years studying advanced math. You only need SQL, Excel, and the ability to tell a story with numbers. Entry-level positions start between $70,000 to $85,000 if you have in-demand skills. That's already close to 6 figures right out the gate. But here's the thing that no one talks about. Data analyst jobs give you the real experience with actual business problems. You learn how companies use data to make decisions. You understand what questions matter and what don't. You build relationships with stakeholders who will later advocate for your promotion. And when you're ready to move into data science or machine learning, you're not some academic trying to prove theoretical knowledge. You're an insider who already understands the business. Many data analysts see faster salary bumps in their second job than traditional college grads climbing the corporate ladder because you're not just another resume. You've already proven you can deliver value. So stop overthinking the perfect learning path into data and get hired as an analyst first. Then you can branch out once you're getting paid to learn. I've taught thousands of career changers the exact way to do this. And if you're interested in learning how, comment data and I will send you my free roadmap.