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Tests conflict resolution in an analytical setting, especially how you use data, communication, and consensus-building to resolve methodology disputes.
Tests rigor in study design, measurement, and statistical practices to support trustworthy results.
Tests planning, prioritization, and execution under resource and timeline pressure.
Tests stakeholder management and trade-off decisions between research rigor and product delivery.
Tests motivation and fit for mental healthcare technology’s mission and stakeholder needs.
Tests rigor in validating ML models on sensitive, non-linear behavioral data for clinical-adjacent use cases.
Tests communication skills translating statistical results into actionable clinical or stakeholder understanding.
Tests critical thinking and persuasive communication to improve team strategy.
Tests practical data cleaning and robustness techniques for messy clinical behavioral data.
Tests how you handle research disagreements while maintaining collaboration and methodological integrity.
Tests applied statistical programming skills and ability to deliver reliable outputs in production workflows.
Tests experience resolving inconsistencies to produce defensible research conclusions.