Data Scientist Interview Questions

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

Jyoti V. - "Over-fitting of a model occurs when model fails to generalize to any new data and has high variance withing training data whereas in under fitting model isn't able to uncover the underlying pattern in the training data and high bias. Tree based model like decision tree and random forest are likely to overfit whereas linear models like linear regression and logistic regression tends to under fit. There are many reasons why a Random forest can overfits easily 1. Model has grown to its full depth a"See full answer

Kanishkan V. - "I responded with a project that I was a part of during my capstone class. I described how I used HTML, Python, and PostGRESQL in conjunction to create a functioning website using SCRUM."See full answer

Amparo L. - "The reason I want to work at Doordash is because I’m a really hard worker, I never give up and I’m good at delivering stuff to my teachers at school whenever they have something to drop off to them, I look at the paper and then I read the directions given to me on the ipad to drop it off."See full answer

Manaswini D. - "user surveys and interviews: Ask users how well the reactions reflect their feelings. sentiment analysis : Analyze comment sentiment to see if it aligns with reactions. Machine learning classification model: Train models to predict user emotion from post content and compare with selected reactions."See full answer

Jiin S. - "I would use A/B testing to see if the new feature would be incrementally beneficial. To begin the testing, we should define what's the goal of this testing. Let's say the new feature would increase the average number of trade by X. Then randomly assign the clients to two groups, control and test group. Control group doesn't see the new feature and the test group see the new feature. We could also stratified sampling if we want to make sure cover different customer segmentation. During this desig"See full answer

Ali H. - "SQL databases are relational, NoSQL databases are non-relational. SQL databases use structured query language and have a predefined schema. NoSQL databases have dynamic schemas for unstructured data. SQL databases are vertically scalable, while NoSQL databases are horizontally scalable."See full answer

Rick E. - " O(n) time, O(1) space from typing import List def maxsubarraysum(nums: List[int]) -> int: if len(nums) == 0: return 0 maxsum = currsum = nums[0] for i in range(1, len(nums)): currsum = max(currsum + nums[i], nums[i]) maxsum = max(currsum, max_sum) return max_sum debug your code below print(maxsubarraysum([-1, 2, -3, 4])) `"See full answer

Guilherme F. - "A much better solution than the one in the article, below: It looks like the ones writing articles here in Javascript do not understand the time/space complexity of javascript methods. shift, splice, sort, etc... In the solution article you have a shift and a sort being done inside a while, that is, the multiplication of Ns. My solution, below, iterates through the list once and then sorts it, separately. It´s O(N+Log(N)) class ListNode { constructor(val = 0, next = null) { th"See full answer

Rishi G. - "Problem Statement: The Fibonacci sequence is defined as F(n) = F(n-1) + F(n-2) with F(0) = 1 and F(1) = 1. The solution is given in the problem statement itself. If the value of n = 0, return 1. If the value of n = 1, return 1. Otherwise, return the sum of data at (n - 1) and (n - 2). Explanation: The Fibonacci sequence is a series of numbers where each number is the sum of the two preceding ones, typically starting with 0 and 1. Java Solution: public static int fib(int n"See full answer

Surbhi G. - "Deep Learning is a part of Artificial Intelligence, it's like teaching the machine to think and make decisions on its own. It's like how we teach a child the concept of an apple - it's round, red, has a stem on top. We show them multiple pictures of apples and then they understand and can recognize an apple in future. Similarly, we feed lots of data to the machine, and slowly, it starts learning from that data, and can then make relevant predictions or decisions based on what it has learnt. A co"See full answer

Farza S. - "It is the smallest level of significance at which the null hypothesis gets rejected"See full answer

Meenakshi D. - "BETWEEN and HAVING clauses in SQL serve different purposes: 1. BETWEEN Clause Used to filter rows based on a range of values. Works with numeric, date, or text values. Can be used with WHERE or HAVING clauses. The range includes both lower and upper bounds. Example: Filtering employees with salaries between 30,000 and 50,000 `SELECT * FROM Employees WHERE salary BETWEEN 30000 AND 50000;` 2. HAVING Clause Used to filter **groups"See full answer

Dev S. - "Clarfying questions : When we say a decrease in users adding the bank accounts. I would like to understand how the users making payments within Venmo I assume they are either using their credit cards/debit cards? I would like to understand why the Adding of Bank Accounts is integral to Venmo since the users are using the debit card and Credit Cards. My understanding is when the payments happen through debit cards rails Venmo pays higher interchange fees and to Reduces any losses incurred"See full answer

Ilnur I. - "I can try to summarize their discussion as I remembered. Linear regression is one of the method to predict target (Y) using features (X). Formula for linear regression is a linear function of features. The aim is to choose coefficients (Teta) of the prediction function in such a way that the difference between target and prediction is least in average. This difference between target and prediction is called loss function. The form of this loss function could be dependent from the particular real"See full answer