Role·Roles & Org·Added 1 month ago

Data scientist

Also known as: DS, applied data scientist, senior data scientist

A role focused on extracting insight and building predictive models from data. Predates the LLM era but remains central in organizations where AI is applied to business data, fraud detection, recommendations, and forecasting.

Data scientist became a prominent title around 2012 and was famously called 'the sexiest job of the 21st century' by Harvard Business Review. The core work: clean and explore data, build statistical or machine learning models, and communicate findings to decision-makers. In many organizations, the data scientist was the first person doing anything resembling AI.

The role has evolved but not disappeared. In the LLM era, data scientists often own the evaluation and measurement side of AI work: designing benchmarks, analyzing model outputs at scale, and detecting when deployed systems drift from expected behavior. They also lead the work of training classifiers or recommendation models that sit alongside or beneath large language models in production pipelines.

Where the role is changing is in the expectation to work with unstructured data and language models directly. A data scientist in 2025 is likely comfortable with embeddings (numerical representations of text or images that let you measure similarity), vector databases, and fine-tuning workflows, not just the traditional Python-and-pandas stack. The title still shows up in almost every AI team, though the actual scope varies widely by organization.

This definition is AI-generated and refreshed weekly. It may contain inaccuracies. Use your own judgment, especially for production decisions.

Related terms