In technical interviews at top-tier firms like Goldman Sachs, candidates face intense pressure and must provide high-quality answers within a limited time frame. Even if you've practiced countless LeetCode problems, the stress of a live interview, the ticking clock, and an unfamiliar question can leave you blank. In these situations, technical skills alone aren't enough. What truly helps is having real-time support to ensure you don’t make mistakes. Today, we will explore how CSOAHELP remote interview assistance helped a candidate successfully navigate the Goldman Sachs interview process and secure an offer, despite facing high-pressure challenges.

Before the interview, A had spent significant time preparing, but the Goldman Sachs interviewer wasted no time and jumped straight into the technical question.

Problem Statement
Given a list of student test scores, find the best average grade.
Each student may have more than one test score in the list.

Example Input

[
    ["Bobby", "87"],
    ["Charles", "100"],
    ["Eric", "64"],
    ["Charles", "22"]
]

Expected Output

87

The problem seemed simple, but under pressure, A couldn't immediately determine the optimal approach. At this moment, the CSOAHELP remote interview assistance team provided a well-structured solution outline on the secondary screen, allowing A to articulate the solution clearly to the interviewer.

CSOAHELP Provided Solution Framework (A Repeats Directly)
We can use a hash table (dictionary) to store a list of scores for each student, then iterate through the dictionary to compute the average score and find the highest one. First, we create a dictionary where the key is the student’s name and the value is a list of scores. Next, we iterate through the input data and add scores to the corresponding student’s list. Then, we compute each student’s average score, applying the floor function. Finally, we return the highest average score, and if the input is empty, we return 0.

The interviewer nodded in agreement and asked A to implement the solution in code.

Even with a clear understanding of the approach, coding under pressure can lead to mistakes. To ensure A could implement it correctly and efficiently, CSOAHELP provided the complete solution, allowing A to either recite the logic or quickly type it out if needed.

CSOAHELP Provided Full Python Solution (A Directly Inputs It)

from collections import defaultdict
import math

def bestAverageGrade(scores):
    if not scores:
        return 0  

    student_scores = defaultdict(list)

    for name, score in scores:
        student_scores[name].append(int(score))  

    best_avg = float('-inf')

    for name, grades in student_scores.items():
        avg = sum(grades) / len(grades)
        best_avg = max(best_avg, math.floor(avg))  

    return best_avg

A typed out the solution in front of the interviewer and ran test cases to ensure correct output. The interviewer was satisfied but then moved on to the real challenge: the follow-up questions.

Goldman Sachs interviews don’t just assess coding ability; they emphasize how candidates think and solve real-world engineering problems. The interviewer then asked: “What if the dataset is enormous, containing millions of student records? Will your code still run efficiently?”

A hesitated, unsure how to frame the response under pressure. At that moment, CSOAHELP's remote assistance team swiftly provided a detailed response, which A could recite immediately.

CSOAHELP Provided Answer (A Repeats It Directly)
The current time complexity is O(N) since we iterate over the input twice—once to store scores and once to compute averages. The space complexity is O(N) because we store all student scores in memory. For very large datasets, we can optimize the storage approach using a rolling average (online computation) instead of keeping all scores in memory.

Specifically, we can:

• Maintain a rolling average (current_avg) instead of storing all scores.
• Use a counter (count) to track the number of scores per student.
• Update the average with each new score using new_avg = ((current_avg * (count - 1)) + new_score) / count.

This allows us to achieve O(1) space complexity while keeping the time complexity at O(N).

The interviewer was impressed and followed up with another question: "How would you parallelize this computation across multiple files containing student records?"

A was momentarily taken aback, but CSOAHELP promptly provided the complete response, allowing him to deliver a confident answer.

CSOAHELP Provided Answer (A Repeats It Directly)
Since student records might be distributed across multiple files, we can use the MapReduce model to process them in parallel.

• Map phase: Distribute student records across multiple worker threads, where each worker independently computes the average scores for its assigned students.
• Reduce phase: Aggregate the results from all workers and extract the highest average score.

With this approach, we can efficiently process large-scale data in a distributed environment while improving computational speed.

The interviewer appeared highly satisfied with this answer, and A maintained his composure, successfully passing this stage of the assessment.

Reflecting on the interview, if A had relied solely on personal preparation, he might have struggled with:

• Implementation errors that could have raised concerns from the interviewer.
• Follow-up questions that required quick, structured responses.
• Scaling discussions that needed a clear and confident explanation.

However, with CSOAHELP's real-time guidance, A delivered well-structured answers, handled follow-up questions smoothly, and ultimately secured the offer.

Goldman Sachs, Morgan Stanley, J.P. Morgan, and Google interviews are not just about solving algorithmic problems; they test how well candidates remain composed under pressure, explain their solutions clearly, handle follow-ups effectively, and avoid minor mistakes. If you’re worried about losing an opportunity due to nerves or unstructured responses, CSOAHELP’s remote interview assistance ensures that you stay on track, articulate strong answers, and secure the job you deserve.

Still hesitating? Let our expert team support you in your most critical interviews. Contact CSOAHELP today and make sure you walk away with an offer!

经过csoahelp的面试辅助，候选人获取了良好的面试表现。如果您需要面试辅助或面试代面服务，帮助您进入梦想中的大厂，请随时联系我。

If you need more interview support or interview proxy practice, feel free to contact us. We offer comprehensive interview support services to help you successfully land a job at your dream company.