United Airlines data analyst candidates report a recruiter screen, SQL-heavy technical questions, case studies and behavioral conversations with managers. Here is what each stage looked like and how to prepare.
$83K
Avg. Base Comp
$95K
Avg. Total Comp
3-4 rounds
Typical Rounds
4-6 weeks
Process Length
Candidates describing United Airlines analyst interviews point to the same mix: a recruiter or HR screen, SQL, a case or estimation exercise, and behavioral conversations with managers. Only five reports are available, and they cover several analyst levels, so treat the details as a sample.
SQL is the most concrete technical topic. One candidate who received an offer described four to five medium-to-hard SQL questions on joins, aggregations and filtering, and said interviewers cared about explaining trade-offs. Another was asked about lead and lag, and a third reported CTEs and window functions. Python (numpy and pandas) and Excel macros or VBA came up in one account.
Case work appeared in three reports. The offer-stage candidate got a coffee-shop profitability prompt and was judged on structure, metrics and stated assumptions. Another reported guestimates plus a small case and a question about recent aviation news. A third found the case study unclear and wanted more guidance on what was being assessed.
Behavioral questions appeared in most reports: conflict with colleagues, difficult situations, why United, and detailed walk-throughs of past projects. One senior-level candidate faced about two hours of 30-minute sessions with different teams, so concise stories matter. That candidate was also asked what new idea they would bring to the program, so bring one or two concrete suggestions.
Four of the five candidates did not get offers. One said the role went to an internal candidate, and another described long gaps between rounds. Plan for slow communication and follow up politely.
Synthesized from 5 candidate reports by our editorial team.
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Featured question at United Airlines
Describing a data project and its challenges
| Question | |
|---|---|
| KNN From Scratch | |
| Boarding Times Bias | |
| Employee Salaries | |
| Top 3 Users | |
| User Experience Percentage | |
| Download Facts | |
| Experiment Validity | |
| Weighted Keys | |
| Third Purchase | |
| Button AB Test | |
| Distance Traveled | |
| Normal Distribution Sample | |
| Size of Joins | |
| Manager Team Sizes | |
| Maximum Profit | |
| Bank Fraud Model | |
| Encoding Categorical Features | |
| Network Experiment Design | |
| Assumptions of Linear Regression | |
| Revenue Retention | |
| Google Maps Improvement | |
| Type-ahead Search | |
| Demand Metrics | |
| Type I and II Errors | |
| P-value to a Layman | |
| Christmas Dinner Ingredient Optimization | |
| Reward Experiment | |
| Pre-Launching Shows | |
| One Million Rides |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report starting with a recruiter or HR conversation, sometimes after a referral or LinkedIn outreach. One offer-stage candidate was asked about conflict using the STAR method and to self-rate Excel, SQL and Tableau. Be ready to name the tools you actually used on specific projects.
Several candidates describe a manager conversation centered on behavioral questions and walking through past projects. One was asked what new idea they would bring to the program. Prepare a few concise stories and one or two concrete ideas, since timing and format may vary by team.
Reports describe SQL as the main technical focus, including joins, aggregations, CTEs, and window functions such as lead and lag. One candidate also reported Python with numpy and pandas, plus Excel macros and VBA. Candidates describe the questions as fundamentals rather than tricks, so explaining your reasoning clearly likely matters.
Some candidates report a case study or guestimates, including a coffee-shop profitability prompt. The offer-stage candidate said the focus was breaking down the problem, choosing metrics and stating assumptions. Another found expectations unclear, so ask what the interviewers want to see before you start.
Final stages varied across candidates. One had a call with a senior manager about business context and cross-functional work. Another had about two hours of 30-minute sessions with different teams, mostly behavioral. Another met a department head. Expect your final format to vary and keep answers concise.
