## Problem You have a bonus pool of `total_budget` dollars to distribute among employees. Employees are ranked by performance score. The distribution rules: - Top 10% of employees receive 3x the base share. - Next 20% receive 2x the base share. - Remaining 70% receive 1x the base share. - Base share = `total_budget / weighted_employee_count`. ```python def distribute_bonuses( employees: List[dict], # [{"id": str, "score": float}] total_budget: float ) -> List[dict]: # [{"id": str, "bonus": float}] ... ``` **Example:** ``` employees = [ {"id": "e1", "score": 95}, {"id": "e2", "score": 80}, {"id": "e3", "score": 60}, {"id": "e4", "score": 40} ], total_budget = 10000 # Top 10% (1 emp) -> 3x, Next 20% (1 emp) -> 2x, Rest (2 emps) -> 1x # Weighted total = 3+2+1+1 = 7 shares # base = 10000/7 ~ 1428.57 -> [{"id":"e1","bonus":4285.71}, {"id":"e2","bonus":2857.14}, {"id":"e3","bonus":1428.57}, {"id":"e4","bonus":1428.57}] ``` ## Follow-ups 1. How do you handle ties at the tier boundaries? 2. Ensure the distributed amounts sum exactly to `total_budget` - how do you handle rounding errors? 3. How would you add a minimum bonus guarantee for all employees? 4. Extend to support per-department budget caps.

InterviewDB Experience

Paying Bonuses - Distribute Bonus Pool Based on Performance Tiers

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Interview Experience

Problem You have a bonus pool of total_budget dollars to distribute among employees. Employees are ranked by performance score. The distribution rules: Top 10% of employees receive 3x the base share. Next 20% receive 2x the base share. Remaining 70% receive 1x the base share. Base share = total_budget / weighted_employee_count. Example: Follow-ups How do you handle ties at the tier boundaries? Ensure the distributed amounts sum exactly to total_budget - how do you handle rounding errors? How wou…

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About This Question

This is a candidate experience report from a gusto interview during the phone round.

It covers the following topics: System Design, Coding, Phone, Onsite .

Topics

System Design Coding Phone Onsite

About Gusto Interview Reports

This question was reported by a candidate who interviewed at Gusto. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.

Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Gusto are the higher-signal extractions to take from this report.

For broader preparation context, the Gusto interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.

How To Practice This Type of Question

Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.

Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Gusto reports consistently are the ones worth investing in; one-off niche problems are not.

During Your Gusto Round

Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.

The single most predictive failure mode in Gusto reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.