Big Tech platforms Financial Analyst Interview Loop
Financial analyst is a corporate finance role rather than a data role, and the interview shows it. There's a recruiter call, then a phone screen that's mostly behavioral with a finance question attached. After that come four to five rounds that mix a modeling or business case with several behavioral interviews. Amazon's loop is the one to know, and the hardest. It has Leadership Principles in every round, a Bar Raiser, and a case built on Amazon's own numbers.
Practice by round
Finance and data basics under time. The SQL is on sales, salary and order tables: highest-selling items, bonuses, promotions, and the second-highest salary without ORDER BY. In the real loop there are corporate finance checks too, like how you'd explain a margin change or walk through a variance.
| Question | Difficulty |
|---|---|
| Salary by Education | Easy |
| High Earners in Support Departments | Easy |
| Find the date with the highest opening stock price | Easy |
| Employees With Bonuses | Easy |
| Lowest Priced Orders | Easy |
| Order Details | Easy |
| Average Salaries | Easy |
| Sales Dept Salaries | Easy |
The analysis the case is built on: top sellers and their share, month-over-month change, salary and bonus comparisons by department, and premium versus free accounts. Use SQL where the team does, and spreadsheet logic where it doesn't.
| Question | Difficulty |
|---|---|
| Customer Revenue In March | Medium |
| Top 10 Salaries | Medium |
| Fifth Highest Salary Without TOP or LIMIT | Medium |
| Employees With the Same Salary | Medium |
| Second Highest Salary Without ORDER BY | Medium |
| Highest Salaried Employees By Department | Medium |
| Highest Salary | Medium |
| Second Highest Salary | Medium |
| Employee and Manager Salaries | Medium |
| Highest Salary In Department | Medium |
| Proportion Of Total Spend | Medium |
| Highest Target | Medium |
| Highest Target Under Manager | Medium |
| Common Interests Amongst Users | Hard |
| Price Of A Handyman | Hard |
The business case, the way a platform finance team runs it. You size a program, decide whether it pays back, then present and defend it with your assumptions said out loud. The mini-analyses here are the same math in a data setting, like plan payback and lifetime value, and subscription-plan breakeven. Next to them are estimation and business cases, like doubling the number of ads and how many Big Macs.
| Case study | Difficulty |
|---|---|
| Graph of Sales and Revenue | Easy |
| McD's Big Macs | Medium |
| Estimating Birthdays | Medium |
| Anti-Dentite | Medium |
| Finding Invalid Schools | Medium |
| Meta/Facebook Nicknames | Medium |
| Double the Number of Ads | Medium |
| Finding Invalid Schools | Medium |
| Meta/Facebook Likes | Medium |
| Replacements Recommendation | Medium |
Probability and statistics at the level the case needs: expected value, distributions, margin of error, and when a difference is real.
| Question | Difficulty |
|---|---|
| Margin of Error | Easy |
| Winning on Your First Roll | Easy |
| Random Card | Medium |
| Probability Distribution | Medium |
| Cosine Convolution | Medium |
| More Effective Advertisement | Medium |
| New vs Old Design | Medium |
| Defective Bulbs | Medium |
| Coin Tossing | Hard |
| Fair vs Biased Coins | Hard |
| Spam Emails | Hard |