A data scientist with a background in startups joined a medium to large retail company three years ago. Initially tasked with modernizing a Python application, the project took six months, involving refactoring, containerization, and deployment on an OpenShift cluster. The application, a 5000-line Jupyter Notebook, was crucial for business operations. Over the next two years, the scientist spent time dissecting and rewriting the application’s logic, building classification models, and navigating a corporate reorganization. Despite being promoted to DS Manager, the lack of a clear data strategy and the bureaucratic processes introduced post-reorg left the scientist feeling isolated and uncertain about career growth. The company’s shift towards a more corporate structure has left the data scientist questioning their experience’s adequacy for transitioning to another DS role.
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