Convince Stakeholders: Prioritize Data Science Projects Effectively
Overview
This question evaluates a data scientist's stakeholder influence, cross-functional communication, and prioritization of analytical work under time and resource constraints, with emphasis on translating technical insights into measurable business impact.
DoorDash
Aug 4, 2025, 10:55 AM
Data Scientist
Onsite
Behavioral & Leadership
0
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Behavioral: Influencing Stakeholders and Prioritizing Work
Context
As a data scientist working cross-functionally (e.g., with Product, Operations, Engineering, Marketing), you often need to:
- Translate technical insights into business impact for non-technical partners.
- Prioritize competing analysis/modeling requests under time and resource constraints.
Questions
- Describe a time you successfully convinced non-technical partners to adopt your recommendation.
- How do you prioritize competing data science tasks or product requests?
Guidance
- Use STAR (Situation, Task, Action, Result).
- Highlight stakeholder mapping, communication strategies, and data-driven storytelling.
- Use impact-versus-effort frameworks (e.g., RICE/ICE), confidence, and sequencing logic.
Solution
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