Will AI replace applied machine learning scientists?

Ironically, those who build AI are somewhat susceptible to its automation, as AutoML and LLMs can now write code and tune hyperparameters. However, the 'scientist' aspect—defining problems and ensuring data quality—remains a deeply human cognitive task.

Applied Machine Learning Scientist scores 25/100 — This career is well shielded from AI replacement. Roughly 55% of the tasks in this role could be automated with current and near-future AI.

The US median salary for a applied machine learning scientist is about $155,000 per year, with projected employment growth of +23% over the next decade (much faster than average).

Automating hyperparameter tuning and model selection using AutoML frameworks. Writing boilerplate Python code for data ingestion and preprocessing pipelines. Generating basic data visualization plots and summary statistics. Running standard unit tests on model performance metrics.

Applied Machine Learning Scientist has a low AI risk score (25/100) and a +23% 10-year outlook. Compare it with your current job or use the salary calculator to see how a switch would affect your pay.

AI can speed up routine applied machine learning scientist tasks like Automating hyperparameter tuning and model selection using AutoML frameworks. and Writing boilerplate Python code for data ingestion and preprocessing pipelines.. The most resilient workers learn to direct these tools while focusing on the human judgment, creativity and physical work that AI can't easily replicate.