Dataford
Interview QuestionsInterview GuidesExperiencesCoaching
New
Pricing
Get started
Dataford
Popular roles
Software EngineerData AnalystData ScientistData EngineerBusiness AnalystAI EngineerMachine Learning EngineerProduct Manager
Browse
Browse All RolesEvery role hub, from analyst to MLBrowse All CompaniesCompany-specific interview loopsAll Interview GuidesThe full guide library
Top questions by role
Software EngineerData AnalystData ScientistData EngineerBusiness AnalystAI EngineerMachine Learning EngineerProduct Manager
Top questions by skill
SQLPythonStatisticsMachine LearningA/B TestingSystem DesignGenerative AIProduct SenseMetricsBehavioral
Browse all questions →Try a mock interview
Experiences
Practice
Mock InterviewsTimed interview simulations with feedbackCoaching1:1 coaching with people at your target companiesSuccess PathYour 6-week structured planModulesCurated lessons by topicWebinarsTalks from ex-Big Tech data leadsPlaygroundA free-form scratch editor
Learn
BlogInterview strategy and career adviceTech Job Market ReportHiring trends across data and AI rolesFor UniversitiesDataford for career centersAbout DatafordWho we are and how we build
Pricing
Build my plan

Improve Underperforming Model Accuracy

MediumModel Evaluation00:00
Practice interviewer
In session
5 left
00:00

Your question is Improve Underperforming Model Accuracy. Take a moment with it on the right.

Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).

You need to log in / sign up to chat or submit.

Problem

Scenario

You've shipped a model that is underperforming relative to expectations, and the team wants a clear plan to improve it. You need to explain how you would evaluate the current errors, identify likely causes, and decide which changes are most likely to raise performance.

Question

How would you improve the accuracy of a model that is underperforming?

Current Signals

Recall·0.65Macro F1·0.69Precision·0.74Test accuracy·0.76Train accuracy·0.89Validation accuracy·0.78

Representative Context

Anchor your answer in a realistic example such as a Grammarly Editor suggestion classifier, where both false positives and false negatives affect user trust and product value.