Starting a Career in Data Science in the Age of AI

Aspiring data scientists should diversify their experience across various industries like healthcare and government, not just the software industry. Practitioners have a responsibility to educate their organizations on the ethical and effective use of data and models, acting as a safeguard against the misuse of AI. Rather than over-specializing in frontier models, early-career professionals should build a versatile skill set focusing on fundamental problem-solving abilities that are transferable across technologies. Large Language Models (LLMs) should be used cautiously as tools, but professionals must retain the ability to perform tasks manually to ensure quality and continuous learning.