IntermediateBEHAVIORAL
Describe a situation where you worked under the guidance of a more senior data scientist. What specific tasks were you responsible for, what did you learn from that collaboration, and how did you incorporate their feedback into your work?
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Sample Answer

On a churn prediction project for a subscription product, I worked closely with a senior data scientist who was leading the overall solution. The team was five people; my main responsibilities were data cleaning, feature engineering, and building the initial baseline models. I owned the pipeline for 2+ years of behavioral data, creating features around login frequency, support tickets, and plan changes. My first model was a basic logistic regression that got us to about 0.68 AUC. In review, the senior DS pushed me to simplify highly correlated features, add time-based features, and tighten up my cross-validation strategy. I refactored the feature set, implemented time-based CV, and documented every modeling decision. That bumped performance to 0.76 AUC and made the model much more interpretable for the marketing team. The bigger learning for me was how to structure experiments, write clearer analysis docs, and proactively ask for feedback on tradeoffs instead of just on code.

Keywords

Worked under a senior DS on a churn prediction project with a five-person teamResponsible for data pipeline, feature engineering, and baseline modelingIncorporated feedback on feature simplification and time-based validationImproved model AUC from 0.68 to 0.76 and learned better experimentation habits
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