Decagon Interview Questions
The questions to prepare for Decagon interviews, across all roles. Questions from real interview reports rank first. Updated daily.
Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.
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Explain how you manage scope changes during development without losing delivery control, stakeholder alignment, or product quality.
DecagonApproach for building data pipelines that scale in throughput, reliability, and operational visibility.
DecagonExplain how to select metrics, validate predictions, and analyze errors when evaluating a machine learning model.
DecagonTests whether a candidate can explain SOLID and core OOP concepts precisely and apply them in real code.
DecagonExplain a practical approach to fine-tuning an LLM for a specific task, including data, evaluation, and hallucination risks.
DecagonDesign a recommendation system that uses user behavior to retrieve, rank, and re-rank items at scale.
DecagonAggregate monthly sales by product category and use LAG to calculate month-over-month changes.
Total Wine & More
Inc.
Benjamin MooreFilter invalid game events and normalize event names using PostgreSQL string and null handling.
Quantium
Scopely
CarvanaPrepare valid encounter records by trimming text, excluding missing values, and removing invalid charges.
Massachusetts General Hospital
Cognizant
DataVisor