- ensemble methods; normalization vs standardization; loss functions - when to use deep learning vs classical ML; difference between senior versus data scientist; diff. between data analytics vs data scientist;
Sr Data Scientist Interview Questions
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One key question they asked was whether I could design and implement both single and batch inference pipelines while adhering to their MLOps framework. They wanted to see my understanding of production-ready model deployment, automation, and scalability principles.
Do you know what supervised ML is
Mostly around past experience, why you choose CLEO, have you ever used and downloaded our app, etc.
Education and Experience Instances where you helped a team member who was in trouble and pressure Instances where you helped others or gone out of your way Things which worked or which did not work Made a quick decision and why What are the things to add to get approval from senior management for a project Instances where you found new opportunities and proposed it Instances where you volunteered to do something when others were waiting for instructions
past experience, reasons of moving
Graph traversal, binary tree etc
previous projects, skills and experience
Will show you a graph and ask what insights can you find out of it and further questions on that
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