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Meta·Data Scientist·Technical Phone Screen·Senior

SeniorPrefer not to say
Jun 2026Remote

Summary

Technical phone screen for a Data Scientist role at Meta. Two algorithmic problems back to back, both with a competitive programming flavor that felt a bit out of left field for a DS interview. Not a vibe check round at all.

Questions Asked (2)

Q1

You have two arrays representing outbound and return ticket prices indexed by day. Design an algorithm to find the minimum total cost of a round trip where the departure day comes before the return day. Analyze time and space complexity and walk through any optimizations.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

My first instinct was brute force, nested loops, O(n²), and I actually said that out loud which I think was fine.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints and edge cases, then propose a brute-force solution and optimize it using a single pass with a running minimum. Discuss time and space complexity trade-offs and potential further optimizations like early termination or parallelization.

Pro tip: Demonstrate awareness of real-world data by mentioning that ticket prices can fluctuate and that the algorithm should handle large arrays efficiently, perhaps by discussing streaming or distributed computation if the dataset is huge.

1. Clarify the problem

Confirm that departure day must be strictly before return day, arrays are 1-indexed or 0-indexed, and that we need the minimum sum of outbound[i] + return[j] with i < j. Discuss edge cases like empty arrays or no valid pair.

2. Brute-force approach

Propose checking all valid pairs (i, j) with i < j, computing the sum, and tracking the minimum. This takes O(n^2) time and O(1) space.

3. Optimized single-pass solution

Iterate through the arrays once, maintaining the minimum outbound price seen so far. For each day j, compute min_outbound + return[j] and update the global minimum. This reduces time to O(n) and space to O(1).

4. Analyze complexity and trade-offs

Explain that the optimized solution is optimal for a single machine, but if the arrays are extremely large, consider parallelizing by splitting the array and combining results, or using a streaming approach if data arrives sequentially.

5. Discuss extensions and edge cases

Mention handling of missing data, negative prices (if allowed), and the possibility of multiple trips. Also, note that the algorithm can be adapted to find the actual days, not just the cost.

Key Points to Mention

  • Time complexity: O(n) for the optimized solution, O(n^2) for brute-force.
  • Space complexity: O(1) extra space for the optimized solution.
  • The importance of maintaining a running minimum of outbound prices.
  • Edge cases: empty arrays, no valid pair, large input sizes.
  • Potential optimizations: early termination if a very low price is found, parallel processing for big data.
  • Real-world relevance: ticket prices can be volatile, so the algorithm should be efficient and scalable.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

Given an integer k, generate all k-digit numbers that look identical after a 180-degree rotation. Explain your algorithm, its complexity, and how you handle edge cases.

Algorithms & Data Structures
Author's notes

Strobogrammatic numbers.

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AI HintsAI Generated

Suggested Approach

Clarify the definition of a strobogrammatic number and the allowed digits (0, 1, 6, 8, 9). Then present a recursive construction that builds numbers from the outside in, handling the no-leading-zero constraint. Finally, analyze time and space complexity and discuss edge cases like k=0, k=1, and even/odd k.

Pro tip: Mention that this is a classic strobogrammatic number problem and that the same recursive pattern can be adapted to find the k-th such number or count them, showing you understand the underlying structure beyond just generating all.

1. Clarify the problem and constraints

Define what 'look identical after 180-degree rotation' means: digits must map to valid digits (0→0, 1→1, 6→9, 8→8, 9→6) and the number must not have leading zeros. Confirm that k-digit numbers cannot start with 0.

2. Identify the recursive structure

Observe that a k-digit strobogrammatic number can be formed by placing a valid pair of digits at the ends and recursively constructing the inner (k-2)-digit number. For odd k, the middle digit must be one of 0, 1, or 8.

3. Design the algorithm

Implement a recursive function that builds numbers from the outside in. At each step, choose a valid pair (or single middle digit for odd length), ensuring the first digit is not 0. Collect results when the desired length is reached.

4. Analyze complexity and edge cases

Time complexity is O(5^{k/2}) since each pair has up to 5 choices. Space complexity is O(k) for recursion depth plus output storage. Handle edge cases: k=0 (return empty list or ['']), k=1 (return ['0','1','8']), and ensure no leading zeros for k>1.

5. Discuss extensions and optimizations

Mention iterative BFS/DFS alternatives, or how to generate only the k-th number without generating all. Also note that the same logic applies to counting strobogrammatic numbers.

Key Points to Mention

  • Valid digit mappings: 0↔0, 1↔1, 6↔9, 8↔8, 9↔6.
  • No leading zeros for k>1; for k=1, 0 is allowed.
  • Recursive construction from outside in, with special handling for odd length (middle digit ∈ {0,1,8}).
  • Time complexity O(5^{⌈k/2⌉}) and space complexity O(k) for recursion.
  • Edge cases: k=0, k=1, and ensuring the first digit is not 0.
  • Potential optimizations: iterative approach, pruning, or generating the k-th number directly.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.