Company: Bytedance

Position: Data Scientist

Location: nan

Level: Mid-level

Outcome: NA

How was the interview process? What was it like?

The interview was quite great. All the people that I interviewed were PHD holders. In all the interviews the approach to the question was tested more than getting the correct solution

What technical questions were asked?

Python / Pandas, Data Structures and Algorithms, SQL / Analytics, ML Implementation/Engineering System Design, Probability, Modeling and ML Knowledge, Product Metrics and Analytical

What was one of your solutions?

First Solution is the brute force approach

Loop through all the elements and find the element's index

def get_ele_index(arr, target):

    out = -1

    for i in range(len(arr)):

        if arr[i] == target:

            out = i

    return out

For solving it in o(logn) you can use binary search

First binary search for finding the pivot

Then binary search again for finding the element

def find_pivot(arr, low, high):

    mid = int((low + high)/2)

    if arr[mid] > arr[mid+1]:

        return mid+1

    else:

        if arr[low] > arr[mid]:

            find_pivot(arr, low, mid)

        else:

            find_pivot(arr, mid, high)

def binary_Search(arr, ele, low, high):

    mid = int((high+low)/2)

    print(arr, mid, arr[mid], ele, arr[mid] == ele)

    if arr[mid] == ele:

        return mid

    elif arr[mid] > ele:

        mid = binary_Search(arr, ele, low, mid)

    else:

        mid = binary_Search(arr, ele, mid, high)

    return mid

def find_element(arr, ele):

    pivot_index = find_pivot(arr, 0, len(arr)-1)

    print(pivot_index, arr)

    if ele < arr[-1]:

        return binary_Search(arr, ele, pivot_index, len(arr)-1)

    else:

        return binary_Search(arr, ele, 0, pivot_index)