Prepare for and practice interview questions from Bloomberg L.P. across topics like Algorithms, Python, SQL and more.

Bloomberg L.P. Interview Questions

Bloomberg L.P. Interview Guides

Data Structures & Algorithms

Find the missing integer from a array of consequtive integers

Find the Missing Number

Given an integer N, write a function that returns all of the prime numbers up to N

Prime to N

String Subsequence

Write a function to determine whether or not two rectangles overlap.

Rectangle Overlap

Given an array and a target integer, write a function that returns the indices of two integers in the array that add up to the target integer.

Target Indices

Machine Learning

Coefficients of Logistic Regression

Bank Fraud Model

Decision Tree Evaluation

Bias vs. Variance Tradeoff

Addressing imbalanced data in machine learning through carefully prepared techniques.

Data Preparation for Imbalanced Data

Statistics

What are the assumptions of linear regression?

Assumptions of Linear Regression

What are confidence intervals and how are they useful

Confidence Interval Explanation

What is the difference between Logistic and Linear Regression?

Linear vs Logistic Regression

Brainteasers

How would you answer when an Interviewer asks why you applied to their company?

Why Do You Want to Work With Us

What do you tell an interviewer when they ask you what your strengths and weaknesses are?

Your Strengths and Weaknesses

Product Sense & Metrics

Docs Metrics

WhatsApp Metrics

When an interviewer asks a question along the lines of:

<ul>
<li>What would your current manager say about you? What constructive criticisms might he give?</li>
<li>What are your three biggest strengths and weaknesses you have identified in yourself?</li>
</ul>

How would you respond?

When asked about your strengths in an interview, what is an effective way to respond?

When asked about your strengths in an interview, what is an effective way to respond?

Your Strengths and Weaknesses I

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Which of the following is an acceptable strategy when discussing weaknesses in an interview?

Your Strengths and Weaknesses II

When an interviewer asks you a question along the lines of:

<ul>
<li>Why did you apply to our company?</li>
<li>What are you looking for in your next job?</li>
<li>What makes you a good fit for our company?</li>
</ul>

How should you respond?

When asked 'What are you looking for in your next job?' in an interview, how can you tie the company's employee benefits into your response?

When asked 'What are you looking for in your next job?' in an interview, how can you tie the company's employee benefits into your response?

Why Do You Want to Work With Us I

How can company values be used effectively in an interview when asked 'What makes you a good fit for our company?'

How can company values be used effectively in an interview when asked 'What makes you a good fit for our company?'

Why Do You Want to Work With Us II

When responding to the question 'Why did you apply to our company?' during an interview, what aspect should you highlight?

When responding to the question 'Why did you apply to our company?' during an interview, what aspect should you highlight?

Why Do You Want to Work With Us III

Describe a data project you worked on. What were some of the challenges you faced?

Describing a data project and its challenges

Hurdles In Data Projects

Analytics

What are the assumptions of linear regression?

Which assumption of the residuals of the standard linear regression model can not be overcome by increasing the sample size?

Regression assumptions

How would you handle the data preparation for building a machine learning model using imbalanced data?

Given a string, write a function to determine if it is palindrome or not.

Note: A palindrome is a word/string that is read the same way forward as it is backward, e.g. <code>&#39;reviver&#39;</code>, <code>&#39;madam&#39;</code>, <code>&#39;deified&#39;</code> and <code>&#39;civic&#39;</code> are all palindromes, while <code>&#39;tree&#39;</code>, <code>&#39;music&#39;</code> and <code>&#39;person&#39;</code> are not palindromes.

Example:

Input:

<pre tabindex="0" class="chroma"><code>word1 = &#34;tree&#34;
word2 = &#34;radar&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def is_palindrome(word1) -&gt; False
def is_palindrome(word2) -&gt; True
</code></pre>

Given a string, write a function to determine if it is palindrome or not.

String Palindromes

Imagine you are asked to build a machine learning model to decide new loan approvals for a
financial firm. You ask the data department in the company for a subset of data to get started
working on the problem. The data includes different features about applicants such as age,
occupation, zip code, height, number of children, favorite color, etc. You decide to build
multiple machine learning models to test out different ideas before settling on the best one.

How would you explain the bias-variance tradeoff with regards to
building and choosing a model to use?

What is the difference between Logistic and Linear Regression?

When would use one instead of the other in practice?

Create a class named <code>LRUCache</code> that implements the behavior expected of a Least Recently Used (LRU) Cache.

The <code>LRUCache</code> class implements the following methods:

<ul>
<li><code>__init__(self, capacity)</code> - initializes the object and takes in a capacity parameter specifying the maximum capacity of the cache.</li>
<li><code>get_if_exists(self, key) -&gt; Any|None</code> - gets a value based on a key. If the key exists, returns the associated value. If the key has expired or did not exist in the first place, returns <code>None</code>.</li>
<li><code>put(self, key, value)</code> - places a value inside the cache. In the case wherein the cache is full, invalidates the least recently used element. When two keys collide, the older value should be invalidated in place of the new one.</li>
</ul>

Example:

<pre tabindex="0" class="chroma"><code>cache = LRUCache(2)
cache.put(&#34;sample&#34;, 55)
cache.get_if_exists(&#34;sample&#34;) # returns 55
cache.get_if_exists(&#34;key&#34;) # returns None
cache.put(&#34;hello&#34;, 10) 
cache.put(&#34;sample&#34;, 9)
cache.put(&#34;world&#34;, 5)
cache.get_if_exists(&#34;hello&#34;) # returns None
</code></pre>

Notes:

<ul>
<li>It is assured that the value in the <code>put</code> method will never receive a <code>None</code> value. Moreover, it is assured that the capacity will always be &gt; 0.</li>

<li>All operations must be O(1).</li>

<li>Aside from Python’s standard dictionary implementation (<code>{}</code>), you may not use any other built-in data structures.</li>
</ul>

LRU Cache 1

Given an array and a target integer, write a function <code>sum_pair_indices</code> that returns the indices of two integers in the array that add up to the target integer. If not found, just return an empty list.

Note: Can you do it on \(O(n)\) time?

Note: Even though there could be many solutions, only one needs to be returned.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>array = [1 2 3 4] 
target = 5 
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def sum_pair_indices(array, target) -&gt; [0 3] or [1 2]
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>array = [3]
target = 6 
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>Do NOT return [0 0] as you can&#39;t use an index twice.
</code></pre>

Find if there is a path from a starting point to an ending point in a walled maze

Pathfinder in Maze

Write a Python function called <code>longest_increasing_subsequence</code> that takes a list of integers as input and returns as output the length of the longest increasing subsequence in the list.

Note: An increasing subsequence is a subset of a list where the elements are in strictly increasing order. The subsequence does not have to be contiguous or unique.

<h3>Example:</h3>

Input:

<pre tabindex="0" class="chroma"><code>nums = [10, 9, 2, 5, 3, 3, 7, 101, 18]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>4
</code></pre>

Explanation:

The longest increasing subsequence is <code>[2, 3, 7, 101]</code>, for a total length of 4.

Find the longest increasing subsequence in a list of integers.

Longest Increasing Subsequence

Let’s say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service in addition that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

How would we build this model?

Let’s say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

Which statement is true?

Let's say that you work at a bank that wants to build a model to detect fraud on the platform.

The bank wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction in order for the customer to approve or deny the transaction with a text response.

Which statement is true?

Given an integer <code>N</code>, write a function that returns a list of all of the prime numbers up to <code>N</code>.

Note: Return an empty list there are no prime numbers less than or equal to <code>N</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>N = 3
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def prime_numbers(N) -&gt; [2,3]
</code></pre>

<h1>Binary Tree Validation</h1>

You are given the root of a binary tree. You need to determine if it is a valid binary search tree (BST).

A valid BST is defined as follows:

<ul>
<li>The left subtree of a node contains only nodes with values less than or equal to the node’s value.</li>
<li>The right subtree of a node contains only nodes with values greater than or equal to the node’s value.</li>
<li>Both the left and right subtrees must also be binary search trees.</li>
</ul>

Given the function <code>def is_valid_bst(root: Node) -&gt; bool:</code>, return True if the binary tree is a valid BST. Otherwise, return False.

<h3>Example:</h3>

Input:

<img src="/s3/questions/9664817c-3e12-4a40-9236-8382b13f55a0.png" alt="image"/>Converted Binary Tree.png

Output:

<pre tabindex="0" class="chroma"><code>def is_valid_bst(Node(3)) -&gt; True
</code></pre>

Given the root node, verify if a binary search tree is valid or not.

Binary Tree Validation

How would you convey insights and the methods you use to a non-technical audience?

Making data-driven insights actionable for those without technical expertise

Simple Explanations

Let’s say you are working on Google Docs. A product manager comes to you and asks how the product is doing. 

What are the top five metrics that you would start tracking to understand the health of Google Docs?

The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding ones, usually starting with 0 and 1. It is often used in algorithm examples, and is defined by the following formula: F(n) = F(n-1) + F(n-2), with F(0) = 0 and F(1) = 1.

Your task is to implement the Fibonacci algorithm in three different methods:
1. Recursively
2. Iteratively
3. Using Memoization

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>n = 5
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>fibonacci(n) -&gt; 5
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>n = 10
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>fibonacci(n) -&gt; 55
</code></pre>

The Fibonacci sequence starts as follows: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55…

This question requires the implementation of the Fibonacci sequence using three different methods: recursively, iteratively, and using memoization.

Implementing the Fibonacci Sequence in Three Different Methods

Let’s say you’re a data engineer at Fidelity Investments, and you’re running a SQL query on a cloud-based data warehouse. All cluster resources and network health metrics look normal, but the query is still taking over 10 minutes to complete.

How would you go about diagnosing and improving the performance of this query?

How would you diagnose and speed up a slow SQL query when system metrics look healthy?

Slow SQL Query

Query Optimization

Let’s say you work as a data scientist at a bank.

You are tasked with building a decision tree model to predict if a borrower will pay back a personal loan they are taking out.

<ol>
<li>How would you evaluate whether using a decision tree algorithm is the correct model for the problem?</li>

<li>Let’s say you move forward with the decision tree model. How would you evaluate the performance of the model before deployment and after?</li>
</ol>

What is a confidence interval for a statistic? Why is it useful to know the confidence interval for a statistic and how do you calculate it?

You have an array of integers, <code>nums</code> of length <code>n</code> spanning <code>0</code> to <code>n</code> with one missing. Write a function <code>missing_number</code> that returns the missing number in the array.

Note: Complexity of \(O(n)\) required.

Example:

Input:

<pre tabindex="0" class="chroma"><code>nums = [0,1,2,4,5] 
missing_number(nums) -&gt; 3
</code></pre>

Given a list of integers, identify all the duplicate values in the list. Assume that the list can contain both positive and negative numbers, and the order of the list does not matter. A number is considered a duplicate if it appears more than once in the list. Return a list of the duplicate numbers.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1, 2, 3, 1, 2, 3]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>find_duplicates(nums) -&gt; [1, 2, 3]
</code></pre>

The numbers 1, 2, and 3 all appear more than once in the list, so they are considered duplicates.

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1, -1, 2, 3, 3, -1]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>find_duplicates(nums) -&gt; [-1, 3]
</code></pre>

The numbers -1 and 3 both appear more than once in the list, so they are considered duplicates. Note that the order of the output does not matter.

Example 3:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1, 2, 3, 4, 5]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>find_duplicates(nums) -&gt; []
</code></pre>

None of the numbers in the list appear more than once, so there are no duplicates.

This problem involves identifying duplicate numbers in a list of integers. The function should return a list of the duplicate numbers.

Find Duplicate Numbers in a List

Write a function <code>fib</code> which takes an integer <code>n</code> and returns the nth fibonacci number. For this question, <code>fib</code> MUST be recursively defined.

Note: <code>for</code> and <code>while</code> keywords are disabled for this question, as well as <code>functools</code>. Any workarounds around this restriction is prohibited.

Example:

Input:

<pre tabindex="0" class="chroma"><code>n = 4
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def fib(n) -&gt; 3
# the sequence is [1, 1, 2, 3, 5, 8...]
</code></pre>

Implement a dynamic recursive fibonacci function.

Impossibly Iterative Fibonacci

Given a string <code>str</code> of any length, write an algorithm <code>max_repeating</code> to return which character has the longest string of continuous repetition.

If two characters are tied for most continuous repetition, return the character whose longest continuous repetition occurs earliest in <code>str</code>.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>str = &#39;aabbaaccbbbaa&#39;
def max_repeating(str) -&gt; b
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>str = &#39;adccccbbbbc&#39;
def max_repeating(str) -&gt; c
</code></pre>

Most Repetition

What do you think are the most important metrics for WhatsApp?

What is the optimal strategy for reducing customer churn rate in a messaging platform like WhatsApp?

What is the optimal strategy for reducing customer churn rate in a messaging platform like WhatsApp?

You are given a binary tree of unique positive numbers. Each node in the binary tree is represented as a dictionary with the following keys:

<ul>
<li><code>data</code>: integer value stored in the node</li>
<li><code>left</code>: reference to the left child (or <code>None</code>)</li>
<li><code>right</code>: reference to the right child (or <code>None</code>)</li>
</ul>

<pre tabindex="0" class="chroma"><code>node = {
 &#34;data&#34;: 6,
 &#34;left&#34;: {
 &#34;data&#34;: 3,
 &#34;left&#34;: {...},
 &#34;right&#34;: {...}
 },
 &#34;right&#34;: {
 &#34;data&#34;: 9,
 &#34;left&#34;: {...},
 &#34;right&#34;: {...}
 }
}
</code></pre>

Given two node values as input (<code>value1</code> and <code>value2</code>), write a function to return the value of the nearest common ancestor (lowest node in the tree that has both nodes as descendants).

Note: If one of the nodes doesn’t exist in the tree, return <code>-1</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code># Diagram of the binary tree
&#39;&#39;&#39;
 6 
 / \ 
 3 9 
 / \
 2 11
 / \
 5 8
&#39;&#39;&#39;
value1 = 8
value2 = 2
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>common_ancestor(root,value1,value2) -&gt; 3
</code></pre>

Explanation:

<ul>
<li>Ancestors of <code>8</code>: <code>11 → 3 → 6</code></li>
<li>Ancestors of <code>2</code>: <code>3 → 6</code></li>
<li>Common ancestors: <code>3</code> and <code>6</code></li>
<li>The nearest common ancestor is <code>3</code>.</li>
</ul>

Write a function to return the value of the nearest node that is a parent to both nodes.

Nearest Common Ancestor

How would you interpret coefficients of logistic regression for categorical and boolean variables?

Why is one-hot encoding recommended for categorical variables in logistic regression models?

Why is one-hot encoding recommended for categorical variables in logistic regression models?

Let’s say you’re interning at a fintech startup that’s building a platform for online games of chance. During testing, one of your simulations flips a coin 10 times and gets 8 tails and 2 heads.

How would you determine if the coin is fair, and what statistical approach would you use to support your conclusion?

How would you assess if a coin is fair after observing 8 tails in 10 flips?

Fair Coin

Probability

Write a Python function called <code>group_anagrams</code> that takes a list of strings as input and returns a list of lists, where each inner list contains a group of anagrams that were present in the input list.

An anagram is a word or phrase formed by rearranging the letters of a different word or phrase, using all the original letters exactly once.

Note: Each of the inner lists should be ordered alphabetically and contain no duplicate values

<h3>Example:</h3>

Input:

<pre tabindex="0" class="chroma"><code>words = [&#34;eat&#34;, &#34;tea&#34;, &#34;tan&#34;, &#34;ate&#34;, &#34;nat&#34;, &#34;bat&#34;]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>[ 
 [&#34;nat&#34;,&#34;tan&#34;],
 [&#34;ate&#34;,&#34;eat&#34;, &#34;tea&#34;],
 [&#34;bat&#34;]
]
</code></pre>

Explanation:

In the example, the words “eat”, “tea”, and “ate” are anagrams of each other, as are the words “tan” and “nat”. The word “bat” does not have any anagrams in the input list, and therefore is listed on its own. The function then groups the anagrams together and returns a list of lists representing these groups.

Each of the lists representing a group of anagrams is sorted in alphabetical order.

Identify the groups of anagrams in a list of words

Calculate Moving Average	SQL	Easy
Predict Customer Churn	Machine Learning	Medium
A/B Test Significance	Statistics	Medium
Optimize Query Performance	SQL	Hard
Feature Importance Analysis	Machine Learning	Medium
Clean Missing Data	Python	Easy
Neural Network Architecture	Deep Learning	Hard
Calculate Cohort Retention	SQL	Medium
Bayesian Probability	Statistics	Easy
Recommend Similar Products	Machine Learning	Hard

Bloomberg L.P. Interview Questions

Bloomberg L.P. Interview Guides

Bloomberg L.P. Interview Questions

Challenge

Bloomberg L.P. Salaries by Position

Discussion & Interview Experiences

Discussion & Interview Experiences