← Point72 Asset Management Interview Insights
The dense rank part is what got me initially.
Break the problem into three parts: first compute vote totals per candidate per state, then rank states by distinct vote totals using DENSE_RANK, and finally aggregate tied states alphabetically into place columns. Use window functions and conditional aggregation to pivot the results into the required format.
Pro tip: Explicitly state your assumptions about the schema and clarify how ties should be handled—interviewers value candidates who identify edge cases like ties and nulls before coding.
Confirm the columns in the candidates and results tables, and verify that 'top 3 states' means the three highest distinct vote totals per candidate. Ask about tie-breaking rules and whether states with zero votes should be included.
Write a subquery or CTE that groups the results table by candidate and state, summing the votes to get total votes for each candidate-state pair.
Use DENSE_RANK() OVER (PARTITION BY candidate ORDER BY total_votes DESC) to assign a rank to each state based on distinct vote totals, ensuring ties receive the same rank.
For each candidate, filter to ranks 1–3, concatenate state and votes as 'State (votes)', and use conditional aggregation (e.g., STRING_AGG with CASE) to produce one row per candidate with columns for each place.
Within each rank, sort tied states alphabetically and concatenate them with commas. Ensure the final output includes all candidates, even those with fewer than three states, using LEFT JOINs or COALESCE.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.