Data Scientists extract insights from data to drive business decisions — using statistics, machine learning, and visualization. The role has evolved from pure analytics to include ML model building, experimentation design, and increasingly, LLM application development.
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Yes, though the role has evolved. Pure analytics roles are being augmented by AI tools, but Data Scientists who can build ML models, design experiments, and communicate insights remain highly valued. The intersection of data science and LLM applications is the fastest-growing niche.
Data Analysts focus on SQL, dashboards, and descriptive analytics. Data Scientists additionally build predictive models, run experiments (A/B testing), and use ML. DS roles typically require Python and statistics; DA roles emphasize SQL and visualization tools.
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