Data Society Data Scientist Interview Questions
The questions to prepare for a Data Society Data Scientist interview. Questions from real interview reports rank first. Updated weekly.
Build an imbalanced binary classifier for card fraud detection using class weighting, resampling, and threshold tuning with PR-focused evaluation.
Data SocietyBuild an imbalanced binary classifier for payment fraud detection using cost-sensitive learning, threshold tuning, and precision-recall evaluation.
Data SocietyExplain how to detect and handle NULL values in SQL using filtering, COALESCE, CASE, and business-aware imputation.
Data SocietyExplain common SQL-friendly ways to detect outliers and how to handle them without distorting downstream analysis.
Data SocietyAggregate monthly sales by product category and use LAG to calculate month-over-month changes.
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Benjamin MooreUse joins, CTEs, and CASE logic to flag and fill missing financial fields for Qlik planning records.
QlikCompute daily agent call KPIs and SLA using joins, aggregations, and window ranking in a contact center model.
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Assess whether a large train-to-validation gap indicates overfitting in an imagery triage classifier and recommend how to validate it.
Data SocietyDetermine whether a patient risk classifier is overfitting when training metrics are strong but validation and holdout performance drop materially.
Data SocietyApproach for handling missing values in a pipeline with data quality checks and repeatable transformations.
Data SocietyExplain how to evaluate and reason about rare event prediction when the positive class is extremely uncommon.
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