Interview Questions

Nilanjan D. - "Firstly, congratulations to both the interviewer and interviewee. This was a great learning experience However, being a Full Stack engineer and I was having the following suggestions around the Data Model - Driver & Approval can be two different tables Approval & Document - Approval can be a tuple of (userid,documentid) - comments against a rejection (marks the document which triggers rejection)In this way we can capture the entire history of approval workflow (initiate/pending/appr"See full answer

Ankit kumar S. - "A 25% drop-off rate at sign-up for a new app, especially one from Meta, indicates a significant challenge in onboarding and user retention. To analyze this, consider external, internal, and product-specific factors. Identify Potential Causes: External Factors:Competition: Are other platforms offering a more attractive or simpler signup process? Timing: Is there a recent major event or trend that might be influencing user behavior? User Experience: Is the signup process clunk"See full answer

Ankit kumar S. - " logo Contact Interview Preparation Application Process Career Advancement Onboarding and Orientation Common Interview Questions Dashboard Creation Interview Questions and Answers Dashboard Creation Interview Questions and Answers What is a dashboard? Answer: A dashboard is a visual representation of key performance indicators (KPIs) and other important data, designed to provide a high-level overview of a specific area or business process. It typically uses charts, graphs, and other da"See full answer

Bini T. - "I understand this is more focused on ML. However, I have a system question. If users allow us to access their location, or they send location via text box, could we use CDNs for the search without hitting our database? We only query the database when we have zero information on location. Other questions: does embedding always guarantee information on location? Do we discharge the user images after we return a prediction? I heard the feedback that we should keep it for future learning. What would"See full answer

Kusheta K. - "After cleaning and organizing the data the dataset become retable and ready for analysis. This helped the tame make accurate decision based on clean data"See full answer

Rick E. - " O(n) time from typing import List def generate_parentheses(n: int): res = [] def generate(buf, opened, closed): if len(buf) == 2 * n: if n != 0: res.append(buf) return if opened < n: generate( buf + "(", opened + 1, closed) if closed < opened: generate(buf + ")", opened, closed + 1) generate("", 0, 0) return res debug your code below print(generate_parentheses(1"See full answer

K v K. - "Not my response, just the Points noted, : Show passion for the work - certifications, competitions, etc., Show the contribution to the Org Has relevant work experience Has the resume been crafted for the job opening and aligns with the job opening Resumes typically get 15-20 seconds for review "See full answer

Evan R. - "Can someone explain to me the difference between: WHERE orderdate > currentdate - interval '7 days' and WHERE orderdate BETWEEN CURRENTDATE - INTERVAL '6 days' AND CURRENT_DATE Both give the same result in PostrgreSQL, but only the second one passes the test cases."See full answer

Meenakshi sundaram M. - "Structure: 1. Ask Clarifying Questions 2. Look at external factors 3. Look at Internal factors ( Slice the data aross different cuts and plan accordingly) Clarifying Questions: What's an outbound message? Is it something Linkedin users send among each other? Decline trends: Is the decline steep or gradual? From when, are we seeing this decline (Say since a week, fortnight, month, etc) External Factors: Have we seen any competition led changes/ new campaigns etc? Have we see"See full answer

Anonymous Cat - "Good practice video; however, at minute 6:40 in this video, the interviewer confirmed the app version causes no issue! While the final answer was the app version!"See full answer

Cesar F. - "Outliers are data points that significantly deviate from the majority of the data distribution. They can arise due to various reasons, such as measurement errors, natural variability, or rare events. Outliers can distort statistical analyses and machine learning models, making it crucial to detect and handle them properly."See full answer

Dan D. - "I love the answer and framework, my summary of the interview: it is a slightly modified version of Porter's 5 Forces: User benefit -> Bargaining Power of Buyers Apple benefit -> Talks about the company mission and culture (esp. on the relatively closed eco-system) It was expanded more in the latter half of the interview (SWOT + a bit of Value Chain) Competitive landscape -> Industry Rivalry + Threat of New Entrants + Threat of Substitutes Partnership Impact -> Bargaining Power of"See full answer

Aishwarya J. - "Analytics as a career route was to problem solve and think out of the box , where I would be able to inculcate a data-driven thinking to finding solutions. Establishing a foundation and end to end analytical methodologies for giving recommendations for actionable outcomes useful for internal and external teams relying on these observations. Learning the procedure of how to source unstructured data and clean, impute, introduce variables to build impactful inferences."See full answer

Anonymous Giraffe - "this is not a helpful interview, she seems so unprepared, confusing, unable to netting it out :("See full answer

Saurabh K. - "Goals : Determine if the TV series should be renewed If it should be renewed, how much should Netflix be willing to pay for this series Let's assume that the goal is to maximize subscriber retention and engagement while paying a reasonable amount for the licensing costs that is justified by the value added by the series. Assumptions : The show is exclusive to Netflix for a particular region (for eg. US) It has been on the platform for an year Netflix has subscriber level data around"See full answer

Kevin S. - "The question given is intentionally very open ended. As the key phrases used are "air travel" which can encompass all parts of the journey not just the airport or flight experience & "improve the perception" which doesn't necessarily require fixing the problem (although you'd hope that was part of the conclusion). In addition, the constraints of time (1-year) and resources ($10M) means you must be very prescriptive. As such I think it'd be important to ask the following clarifying questions"See full answer

Jerry O. - "\# Definition for a binary tree node. class TreeNode: def init(self, val=0, left=None, right=None): self.val = val self.left = left self.right = right class Solution: def maxPathSum(self, root: TreeNode) -> int: self.max_sum = float('-inf')"See full answer