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Updated weekly · Last refresh Aug 30

Kabbage Data Scientist Interview Questions

The questions to prepare for a Kabbage Data Scientist interview. Questions from real interview reports rank first. Updated weekly.

48questions
~6htotal time
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1
PipelinesStart here. 3 questions · ~24 min
Fraud Detection Batch vs StreamingMedium

Design a fraud pipeline that compares batch, streaming, and hybrid architectures for 120K tx/sec with sub-300 ms decisions and reconciled hourly tables.

Stream ProcessingETLBatch ProcessingKabbage
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2
Machine Learning8 questions · ~65 min
Bias-Variance Tradeoff in PracticeMedium

Explain the bias-variance tradeoff and how it guides model choice, regularization, and generalization performance.

Cross-ValidationBias-Variance TradeoffRegularizationKabbage
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3
Model Evaluation4 questions · ~32 min
Explain Precision Recall TradeoffEasy

Explain precision versus recall in plain language and how the tradeoff affects product decisions.

PrecisionThreshold TuningRecallKabbage
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4
Metrics5 questions · ~40 min
Diagnose a Metric Drop After LaunchMedium

Investigate why a key KPI moved the wrong way after a product change and separate signal from noise.

Lagging IndicatorsLeading IndicatorsDiagnosisKabbage
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5
Statistics & Probability3 questions · ~24 min
Testing a Conversion Rate DropMedium

Explain how to test whether an observed 5% conversion rate drop is statistically significant in an experiment or before-after comparison.

Hypothesis TestingData AnalysisStatistical SignificanceKabbage
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6
A/B Testing & Experimentation3 questions · ~24 min
Pitfalls in Streaming Experiment AnalysisHard

Identify major online experiment pitfalls and explain how they can bias results in a streaming product A/B test.

Network InterferenceNovelty EffectSample Ratio MismatchKabbage
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7
More topics22 questions · ~178 min
Top Funded Customers by MonthMedium

Tests SQL ranking logic and aggregation for monthly customer funding analytics.

Window FunctionsRankingAggregationsKabbage
Scalable Cheating Detection With NLPHard

Evaluates your NLP approach and scalability thinking for large-scale text comparison.

scalabilityKabbage
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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
SQL Join for Total PaidEasy
Practice
Practice drill

Use GROUP BY and SUM to calculate successful Kabbage Funding payments per customer.

JoinsGroup ByAggregationsKabbage
Running Total Transactions QueryEasy
Practice
Practice drill

Aggregate Kabbage Funding transactions by day, then calculate a cumulative total with a CTE and window function.

Window FunctionsDate FunctionsRunning TotalsKabbage
Find Duplicate Records in SQLEasy
Practice
Practice drill

Use GROUP BY and HAVING to find duplicate patient records in a Johns Hopkins Medicine dataset.

Data WranglingGroup ByHavingEmersonAmazon DSPCareDx
The finish line: interview-readyComplete all 48 questions plus 3 hands-on drills to finish this plan.