Research Collaboration and Scope Questions
Collaborating with product, design, engineering, and stakeholders to define research scope, synthesize findings, and influence decisions. Topics include scoping research to business and product needs, communicating results to different audiences, enabling stakeholders to act on insights, and balancing independence of research with collaborative goals. Interviewers expect examples showing how research influenced product direction and how you managed stakeholder expectations.
HardTechnical
38 practiced
You are negotiating a collaborative research and IP agreement with a university lab. Propose key contract clauses to protect both company and academic interests regarding publication rights (embargoes), IP ownership and licensing, data sharing and permitted uses, confidentiality terms, authorship expectations, and timelines for production integration. Explain the trade-offs of tighter vs looser clauses.
MediumTechnical
34 practiced
Design a mid-size A/B test to measure whether a new model improves long-term retention while controlling for novelty effects and seasonality. Explain the randomization strategy, expected duration, sample size considerations, pre-specification of endpoints, and any post-hoc analyses you would plan.
EasyBehavioral
31 practiced
Describe three practical ways you involve product managers and engineers early in the research planning phase to increase the likelihood that research results will be adopted. For each method, give a concrete example of how it changes the research approach, deliverables, or acceptance criteria.
MediumTechnical
34 practiced
You and a product team disagree on the target metric to optimize: product wants to increase average session length while research believes day-30 retention aligns better with long-term value. Design a process to align on the metric, including experiments you would run to test the causal relationship between these metrics and multi-objective approaches or compromise metrics you might propose.
EasyTechnical
38 practiced
You run exploratory research that yields promising signals but no clear production path. Describe how you would convert the exploratory findings into an actionable MVP for the product team. Include steps for validation, minimal data and feature requirements, an engineering handoff checklist, and criteria for 'good enough' for release.
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