Size an Opportunity and Present It with Clear Visuals
Company: Pinterest
Role: Data Scientist
Category: Analytics & Experimentation
Difficulty: medium
Interview Round: Onsite
You receive a slide deck describing an ambiguous business opportunity and are asked to walk through market or product sizing and choose visualizations for your recommendation. Explain how you would structure the analysis when some inputs are uncertain and the audience includes senior decision makers.
### Constraints & Assumptions
- The deck contains partial data rather than every number needed for a precise forecast.
- You should state assumptions and ranges instead of inventing missing facts.
- The goal is a decision-ready analysis, not the maximum number of charts.
### Clarifying Questions to Ask
- What decision must the audience make, by when, and what alternatives are available?
- What exactly is being sized: users, transactions, revenue, cost savings, or another outcome?
- What unit, geography, time horizon, and eligible population are in scope?
- Which inputs are observed, estimated, or assumed, and which are most uncertain?
- What constraints could prevent the theoretical opportunity from being captured?
### What a Strong Answer Covers
- A sizing equation that moves from an eligible population through adoption, frequency, value, and realistic capture.
- Top-down and bottom-up estimates or another independent triangulation.
- Base, conservative, and optimistic cases with sensitivity to the highest-leverage assumptions.
- Clear separation of total opportunity, serviceable opportunity, expected near-term impact, and costs or risks.
- Visuals selected for specific comparisons, trends, funnels, distributions, or uncertainty, with honest axes and denominators.
- A concise narrative that ends with a recommendation, confidence level, and next evidence to collect.
### Follow-up Questions
1. How would you identify which assumption deserves immediate research?
2. When is a funnel chart more useful than a table?
3. How would you display uncertainty without overwhelming the audience?
4. What if the top-down and bottom-up estimates disagree sharply?
Quick Answer: Structure a data science case that sizes a business opportunity from partial information and presents it to senior decision-makers. Build top-down and bottom-up estimates, test sensitive assumptions, show uncertainty clearly, and choose visualizations that support a recommendation.