{"id":195444,"date":"2025-10-24T08:13:01","date_gmt":"2025-10-24T08:13:01","guid":{"rendered":"https:\/\/www.harnham.com\/?p=195444"},"modified":"2025-10-24T08:13:51","modified_gmt":"2025-10-24T08:13:51","slug":"reskilling-upskilling-what-us-data-professionals-are-doing","status":"publish","type":"post","link":"https:\/\/www.harnham.com\/reskilling-upskilling-what-us-data-professionals-are-doing\/","title":{"rendered":"Reskilling & Upskilling: What US Data Professionals Are Doing"},"content":{"rendered":"

\"\"By Luc Simpson-Kent<\/a>, Managing Consultant \u2013 Harnham US<\/span><\/i><\/p>\n

Candidates want growth. Employers want retention.<\/span><\/h2>\n

And in today\u2019s market, both goals rely on the same thing: continuous learning.<\/span><\/p>\n

The pace of change in data and AI means even the most experienced professionals are going back to school, literally and figuratively.<\/span>
\n<\/span>
\n<\/span>Across the US, data scientists, engineers and analysts are reskilling faster than ever, not just to keep up with new technologies, but to stay relevant in an industry where roles evolve as quickly as the models they build.<\/span><\/p>\n

The rise of the always-learning data professional<\/span><\/h3>\n

In Harnham\u2019s latest <\/span>US Data & AI Salary Guide<\/span><\/i>, a lack of career progression ranked among the top three reasons professionals consider leaving their roles. It\u2019s a clear signal: growth is non-negotiable.<\/span><\/p>\n

At the same time, 67 % of respondents said they view AI positively, and nearly two-thirds already use it in their daily work. That shift isn\u2019t just changing <\/span>what<\/span><\/i> people do, it\u2019s redefining <\/span>how<\/span><\/i> they learn.<\/span><\/p>\n

Many professionals are now stacking certifications across <\/span>cloud architecture, data engineering, and AI\/ML tools<\/b> to strengthen career mobility.<\/span>
\n<\/span>
\n<\/span>Common routes include:<\/span><\/p>\n