OTIS Data Scientist Interview Questions
The questions to prepare for a OTIS Data Scientist interview. Questions from real interview reports rank first. Updated weekly.
Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.
OTISDesign a recommendation system for a product catalog using retrieval, ranking, and feature engineering.
OTISDescribe how your analysis of marketing KPIs led to a meaningful decision and how you tied short-term and long-term metrics together.
OTISDesign an experiment plan to measure whether a new UI feature improves user outcomes without hurting key guardrail metrics.
OTISExplain how to design and evaluate an A/B test for a product feature, including metrics, MDE, sample size, and guardrails.
OTISTests your ability to select appropriate metrics based on task type and business or research goals.
OTISTests ability to solve a nontrivial SQL or data manipulation problem involving spatial contiguity.
OTISTests your product-focused modeling approach for recommendations, including data, objectives, and evaluation.
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Calculate daily session-level funnel conversion rates using CTEs, CASE WHEN, and date functions.
Use joins, CASE WHEN, and date filtering to compare outcome rates before and after a decision.
HarbourVest PartnersCompute top 10 customers by net sales using joins and aggregations, ordering by revenue with deterministic tie-breaking.
Gain Digital
TCS
Zest AI