Data Scientist Interview Questions

Divya R. - "static boolean sudokuSolve(char board) { return sudokuSolve(board, 0, 0); } static boolean sudokuSolve(char board, int r, int c) { if(c>=board[0].length) { r=r+1; c=0; } if(r>=board.length) return true; if(boardr=='.') { for(int num=1; num<=9; num++) { boardr=(char)('0' + num); if(isValidPosition(board, r, c)) { if(sudokuSolve(board, r, c+1)) return true; } boardr='.'; } } else { return sudokuSolve(board, r, c+1); } return false; } static boolean isValidPosition(char b"See full answer

Jayveer S. - "WITH suspicious_transactions AS ( SELECT c.first_name, c.last_name, t.receipt_number, COUNT(t.receiptnumber) OVER (PARTITION BY c.customerid) AS noofoffences FROM customers c JOIN transactions t ON c.customerid = t.customerid WHERE t.receipt_number LIKE '%999%' OR t.receipt_number LIKE '%1234%' OR t.receipt_number LIKE '%XYZ%' ) SELECT first_name, last_name, receipt_number, noofoffences FROM suspicious_transactions WHERE noofoffences >= 2;"See full answer

Tiago R. - "function permute(nums) { if (nums.length <= 1) { return [nums]; } const prevPermutations = permute(nums.slice(0, nums.length-1)); const currentNum = nums[nums.length-1]; const permutations = new Set(); for (let prev of prevPermutations) { for (let i=0; i < prev.length; i++) { permutations.add([...prev.slice(0, i), currentNum, ...prev.slice(i)]); } permutations.add([...prev, currentNum]); } return [...permutations]"See full answer

Anonymous Hornet - "To handle the non-uniform sampling, I'd first clean and divide the dataset into chunks of n second interval 'uniform' trajectory data(e.g. 5s or 10s trajectories). This gives us a cleaner trajectory data chunks, T, of format (ship_ID, x, y, z, timestamp) to be formed. For the system itself, I'd use a generative model, e.g. Variational AutoEncoder (VAE), and train the model's 'encoder' to produce a latent-space representation of input features (x,y,z,timestamp) from T, and it's 'decoder' to pred"See full answer

Srijita P. - "Clarification question: How many subscription plans are offered by Tinder ? If there is more than one subscription plan, then we need to ask is the fluctuation happening across all plans or in a particular one ? Assumption: Let's say lower priced subscription plan is showing the most fluctuation and there are only two types of plans In this subscription plan which age group is showing the most fluctuation (18-24,25-30, 30+ etc) ? Is there any seasonality trend observed (eg: placemen"See full answer

Lucas G. - "I would conduct a sample z-test because we have enough samples and the population variance is known. H1: average monthly spending per user is $50 H0: average monthly spending per user is greater $50 One-sample z-test x_bar = $85 mu = $50 s = $20 n = 100 x_bar - mu / (s / sqrt(n) = 17.5 17.5 is the z-score that we will need to associate with its corresponding p-value. However, the z-score is very high, so the p-value will be very close to zero, which is much less than the standa"See full answer

Mark M. - "I don't have experience working with alot of Biological Scientists. Most of my experience comes with Data Scientists. Described how I used ideation techniques like brainstorming and other creative ways to get people to find common ground. I also mentioned how I like to do survey's before meetings to prompt people and also get unbiased opnions"See full answer

Ruth A. - "Spoiled food In a process I improved, I streamlined how tasks were assigned to reduce delays and confusion."See full answer

Rajeev K. - "I’ve spent over 6 years building and scaling e-commerce products across EMEA and APAC. At Jumia, I led product initiatives on the checkout and payments side. For example, I launched gamified promotions on PDP and checkout that improved engagement and delivered a 2.3x uplift in conversion. I also introduced automated installment payments and order cancellation flows, which not only improved user trust but also reduced complaints by 30% and lowered operational costs. Before that, at Lazada, I work"See full answer