Cognite Data Scientist Interview Questions
The questions to prepare for a Cognite Data Scientist interview. Questions from real interview reports rank first. Updated weekly.
Approach for maintaining data quality and integrity across ETL pipelines.
CogniteFramework for choosing a feature's primary success metric and guardrails before launch.
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Tests understanding of interference, contamination, and operational constraints in experiments.
CogniteTests model selection, hybrid modeling, and domain-informed feature design.
CogniteTests hypothesis testing and correct interpretation of statistical significance.
CogniteDiagnose a post-release KPI drop by separating instrumentation issues from real behavior changes and tracing the problem through the metric hierarchy.
CogniteTests evaluation design under noisy labels and agreement-aware validation.
CogniteTests SQL joins, time-series handling, and practical filtering logic for industrial datasets.
CogniteUse joins, CTEs, aggregations, and CASE logic to flag payment cards with anomalous Lyft trip activity.
LyftUse CTEs, joins, and date aggregation to flag Twitch channels with unusually low daily active viewers.
TwitchCalculate daily session-level funnel conversion rates using CTEs, CASE WHEN, and date functions.