Data Scientist

AI is automating the lower-level modeling and feature engineering steps, reducing demand for data scientists who only run off-the-shelf algorithms. Generative AI tools like ChatGPT and Copilot are accelerating code writing and data exploration, making individual data scientists more productive. However, the bar is rising for strategic judgment—companies now expect data scientists to design complex causal inference studies and own end-to-end production pipelines. Roles focused purely on model training are shrinking, while roles combining data science with product analytics or MLOps are growing. Data scientists who excel at translating business problems into formal analytical frameworks will remain in high demand.