Math Questions at Palantir Technologies: What to Expect

Math matters at Palantir Technologies because their core business—building software for data integration, analysis, and large-scale decision-making—is fundamentally mathematical. The company deals with complex datasets, optimization of logistics, threat detection, and resource allocation. These problems require strong analytical reasoning, comfort with probability, statistics, and discrete mathematics to model real-world systems. The three math questions in their interview (out of approximately 30 total) are not about advanced calculus, but about applied, logical problem-solving. They test your ability to think precisely, identify patterns, and translate a word problem into a structured solution—skills directly used when designing data pipelines or algorithms for clients in government and finance.

What to Expect — types of problems

The math problems typically fall into a few key categories:

• Probability & Statistics: Questions about expected value, conditional probability, distributions, or interpreting statistical claims. Example: "If you sample from a dataset with a known bias, how do you estimate the true mean?"
• Combinatorics & Counting: Problems involving permutations, combinations, or systematic counting. Example: "How many ways can you arrange or select items given specific constraints?"
• Logic & Puzzles: Brain-teasers that require deductive reasoning, often with a mathematical twist. Example: "Using a balance scale only twice, find the heavier coin among eight."
• Basic Number Theory & Modular Arithmetic: Concepts like divisibility, remainders, or properties of integers may appear in data grouping or scheduling problems.

The problems are often presented as word problems. The interviewer is evaluating your thought process—how you clarify assumptions, break down the problem, and communicate your reasoning—as much as the final answer.

How to Prepare — study tips with one code example

1. Review Fundamentals: Refresh core concepts in probability (Bayes' theorem, expected value), combinatorics (nCr, nPr), and logic. You don't need a textbook; use targeted online resources.
2. Practice Word Problems: Work on problems from coding interview platforms that are tagged as "math" or "probability." Practice verbalizing your step-by-step reasoning.
3. Code When Applicable: Some math problems have a computational element. Be ready to write simple, efficient code to simulate a scenario or calculate a result.

A common pattern is using simulation to approximate a probability when an analytical solution is complex to derive. Here's an example of simulating a simple dice game to estimate an expected value.

import random

def simulate_dice_game(trials=1000000):
    total_wins = 0
    for _ in range(trials):
        roll = random.randint(1, 6)  # Roll a fair die
        if roll > 3:  # Win condition: roll a 4, 5, or 6
            total_wins += 1
    estimated_probability = total_wins / trials
    return estimated_probability

print(f"Estimated win probability: {simulate_dice_game():.4f}")

Recommended Practice Order

1. Start with foundational probability and combinatorics problems to rebuild intuition.
2. Move to logic puzzles that require step-by-step deduction.
3. Integrate practice by solving Palantir-specific math questions, focusing on clear communication.
4. If a problem feels computational, practice writing clean, quick code to support your answer.

Practice Math at Palantir Technologies