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    Here Is How I Cracked the Citadel SWE New Grad Interview in 2025

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    Seraphina
    ·September 13, 2025
    ·7 min read
    Here is how I cracked the Citadel SWE New Grad Interview in 2025 and what you need to know

    Landing a Software Engineer role at Citadel as a new grad isn’t just about coding, it’s about strategy, preparation, and understanding how to showcase your skills under pressure. In 2025, I navigated the full interview process, from phone screens to HackerRank challenges to rigorous coding rounds.

    In the live interview itself, I had Linkjob AI running I had Linkjob AI running, visible only to me. Its real-time support gave me instant hints and structured talking points as questions came up, so I could focus on delivering my answers clearly. That live assistance made a huge difference.

    Citadel SWE New Grad Interview Process

    Phone Screening

    Some of the questions I was asked included:

    • What do you currently value most in your career? (things missing from my current role)

    • Why [additional major]?

    • Why [internship company]? Why didn’t you consider returning to [internship employer]?

    • Why the finance industry?

    I felt that hedge funds are indeed sharper and more aggressive. They are definitely not as pleasant and friendly as HR at tech companies.

    OA

    Total: 2 problems, 75 minutes to solve. The problems were completed on HackerRank.

    The first problem was protocol-related. Problems are shown in the image below.

    Technical Phone Screen

    I was given a word list and a prefix s, and asked to write a function that returns all words starting with s. This was a typical trie problem, and the approach was straightforward.

    Virtual Onsite

    There were a total of three coding rounds, interspersed with some behavioral questions. The difficulty level was medium throughout.

    VO Round 1

    The problem involved a 9-grid phone unlock swipe pattern. I had to write a function to calculate the total number of possible patterns. I solved it using DFS/backtracking, and the interviewer seemed reasonably satisfied with my approach.

    VO Round 2

    I was asked to design a ring buffer class that supports multithreaded read/write. I implemented the single-threaded logic but spent some time debugging a small bug. I didn’t have time to fully implement the multithreaded part, but I discussed with the interviewer how I would handle locks and condition variables for thread safety.

    VO Round 3

    The problem involved a 1D board with black and white pieces—black pieces can only move right, white pieces can only move left, and pieces cannot jump over others. I was given a start state and an end state, and asked to determine if it was possible to reach the end state through a series of valid moves. After discussing with the interviewer, I realized it could be solved in O(n) time, since I only needed to return true/false, not the specific sequence of moves.

    In those three coding rounds, I used Linkjob to take screenshots and let the AI generate optimal solutions. Then, I combined those insights with my own understanding to complete the problems. I found it really effective, the generation was fast, and the key points were broken down clearly with thorough bullet-point analysis.

    Stealthy AI Interview Copilot

    BQ

    1. Share an experience where you efficiently drove work forward and achieved goals under tight deadlines and heavy workload.

    2. Describe a situation where there was disagreement within your team, and how you resolved the conflict through communication and coordination to reach consensus.

    3. Give an example of a time when, with limited information, you analyzed the situation and made a critical decision.

    Final Interview

    The final interview at Citadel was overall more behavioral, focusing mainly on my communication logic and the depth of my project experience. It lasted about half an hour, one-on-one, and surprisingly, the atmosphere was quite relaxed.

    The interviewer started by asking me to introduce myself. I mentioned that I enjoy hiking, and it turned out the interviewer also loves hiking, so we chatted a bit about that before getting into the main questions.

    Once we got to the main part, there were three key questions:

    Project Experience: I focused on a financial modeling project, explaining the background, the tools and methods I used, and the impact of the results. I had practiced this several times beforehand, so the interviewer was very satisfied.

    Risk Management Experience: This question was very Citadel-style, since the firm places a strong emphasis on risk. My advice is to prepare specific examples in advance.

    Team Collaboration: I shared an experience where a project initially failed but I helped turn it around. The interviewer immediately said, “That’s a good one.” Stories with ups and downs highlight personal growth, and this was something I had prepared in advance.

    Citadel SWE New Grad Interview Questions

    Here are the real OA and coding interview questions I collected by question type while preparing for my interviews.

    OA Questions

    Coding Problems

    Coding Problem 1

    Given an integer array, find the longest subarray whose sum is 0.

    Solution:

    1. Count existing workdays: Let original_ones record the total number of ‘1’s in the original schedule.

    2. Sliding window traversal: Iterate through each right boundary r, keeping track of the number of ‘0’s in the window (cnt_0) and the number of ‘1’s (ones_in_window). If cnt_0 > k, move the left boundary l rightward until cnt_0 <= k.

    3. Update the longest window: Keep track of the length of the longest valid window (max_len) and the number of original ‘1’s it contains (max_ones_in_window).

    4. Calculate total earnings:

      • segment_earning: Earnings from the longest consecutive segment (fixed salary + consecutive bonus).

      • other_ones_earning: Earnings from the original workdays outside the segment (fixed salary only).

      • Total earnings = segment_earning + other_ones_earning.

    This method runs in O(n) time and O(1) space, efficiently maximizing earnings even for large datasets.

    Coding Problem 2

    You are given:

    1. An array of employees, each with a multiplier representing their speed (time taken to complete a task is multiplier × base task duration).

    2. An array of tasks, each with a base duration (the time it takes for a task if the multiplier is 1).

    When an employee i is assigned a task j, the time to complete it is:

    time_i_j = multiplier[i] * task_duration[j]

    Goal:

    Determine the minimum total time needed to complete all tasks if tasks can be assigned to any employee.

    Notes:

    • You can assume all inputs are positive integers or floats.

    • The output should be the total time required to finish all tasks.

    • There are multiple valid strategies for task assignment, and the optimal solution depends on how tasks are distributed among employees.

    Example Input:

    employees = [1.0, 1.5, 0.8]    # multipliers
    tasks = [4, 2, 6, 3]           # base durations

    Example Output:

    7.6  # minimum total completion time

    Coding Problem 3

    Problem (Topological Sort Variant):

    You are given:

    1. A set of characters (not limited to letters or digits).

    2. A list of dependencies indicating that one character must appear before another in the final order.

    Goal:

    Return any valid ordering of all characters that satisfies all the given dependencies. If multiple valid orderings exist, returning any one of them is acceptable.

    Example Input:

    chars = {'a', 'b', 'c', 'd'}
    dependencies = [('a', 'b'), ('c', 'b'), ('d', 'a')]

    Example Output:

    ['d', 'a', 'c', 'b']   # valid ordering

    Notes:

    • All characters in chars must appear in the output exactly once.

    • Dependencies may form a DAG; if the graph has cycles, no valid ordering exists.

    • The solution should handle arbitrary character types (letters, digits, symbols, etc.).

    Citadel SWE New Grad Interview Preparation

    Preparation Strategies

    1. Practice Math Problems: Many questions are highly mathematical, so focus on practicing algorithm problems and core computer science concepts.

    2. Understand the Company and Role: Be clear about why you are applying to Citadel and be ready to discuss your projects and experiences.

    3. Coding Difficulty: Problems are generally from medium-high to hard on LeetCode.

    4. Practice Recommendations: Focus on medium and hard problems, especially in areas like binary trees, graphs, and dynamic programming.

    5. Focus on your resume: The phone screen centers on your projects.

    6. Be ready for detailed questions: HR may ask, for example, “Which analytical methods did you use?” or “How did you solve problems you encountered?”

    7. Use the STAR method: Organize your experiences in advance using Situation, Task, Action, Result.

    Personal Suggestions

    1. Interview Focus: Citadel places great emphasis on attention to detail, clarity of thought, and logical expression. It’s best to include a touch of personal style in your explanations.

    2. During the Coding Round: Interviewers may ask why you designed a solution a certain way and whether there is room for optimization.

    3. Be proactive: Follow up after completing tests or interviews.

    4. Clarify expectations: Ask politely if you need updates.

    5. Timing matters: Following up 1–2 days after an interview or test keeps you memorable.

    6. Mind your tone: Be polite and avoid excessive reminders.

    FAQ

    How did you approach problems where multiple solutions were possible?

    I always started by comparing the trade-offs: time complexity, space usage, and edge-case coverage. Then I explained my choice to the interviewer before coding, which showed that I wasn’t just coding blindly but making informed engineering decisions.

    How did you handle follow-up “optimization” questions without wasting time?

    After coding a working solution, interviewers often asked for optimizations. I trained myself to immediately identify the bottleneck (e.g., space vs. time), articulate potential improvements in bullet points, and implement only the most feasible optimization within the remaining time. Clear communication of reasoning mattered more than perfect code.