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Harman International Interview Questions

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Machine Learning

Interpret coefficients of logistic regression for categorical and boolean variables

Coefficients of Logistic Regression

How do we deal with the missing square footage data to construct our model

Missing Housing Data

Lasso vs Ridge

Why can the same machine learning algorithm produce different success rates on the same dataset

Same Algorithm Different Success

What are some machine learning methods for building this system

FAQ Matching

Data Structures & Algorithms

Find the missing integer from a array of consequtive integers

Find the Missing Number

Write a function one_element_removed that returns the integer removed from list Y in O(1) space and O(n) time without using set

One Element Removed

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

Write a function to return True if two strings are anagrams of each other and False if they are not

Valid Anagram

Write a function that tests whether a string of brackets is balanced.

The Brackets Problem

Behavioral

Describing a data project and its challenges

Hurdles In Data Projects

Prioritized debt reduction, process improvement, and a focus on maintainability for fintech efficiency

Decreasing Tech Debt

How would you negotiate and resolve disagreements when a client rejects your proposed solution?

Client Solution Pushback

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

Duplicate Rows

Categorize sales based on the amount of sales and the region

Categorize Sales

How would you design a data warehouse for a e-commerce company looking to expand internationally?

International e-Commerce Warehouse

Count total tickets, tickets with agent assignment, and tickets without agent assignment.

Ticket Agent Analysis

Product Sense & Metrics

How would you verify the claim that Facebook is losing young users and what test metrics would you look at

Losing Users

Google Maps Improvement

How would you determine the cause and what would you do with these users

Inactive Users

How would you resolve slow, timing-out keyword searches across multiple database fields?

Search Timeout

Tell me about a data project that didn’t go the way you expected. What did you set out to do, what surprised you, and how did you handle 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>

Let’s say we’re comparing two machine learning algorithms. In which case would you use a bagging algorithm versus a boosting algorithm? 

Give an example of the tradeoffs between the two.

In machine learning, when would you use a bagging algorithm over a boosting algorithm?

In machine learning, when would you use a bagging algorithm over a boosting algorithm?

Bagging vs. Boosting

In which case would you use a bagging algorithm versus a boosting algorithm

Bagging vs Boosting

Say you are tasked with designing a data mart or data warehouse for a new online retailer.

How would you design the system?

Note: Sketch a star schema to explain your design.

Design a data warehouse for a new online retailer

Retailer Data Warehouse

Data Modeling

There are two lists, <code>list X</code> and <code>list Y</code>. Both lists contain integers from <code>-1000</code> to <code>1000</code> and are identical to each other except that one integer is removed in <code>list Y</code> that exists in <code>list X</code>.

Write a function <code>one_element_removed</code> that takes in both lists and returns the integer that was removed in \(O(1)\) space and \(O(n)\) time without using the python set function.

Example:

Input:

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

one_element_removed(list_x, list_y) -&gt; 3
</code></pre>

Which of the following methods would be the most efficient way of identifying what element is not included in two lists of integers that differ by a single element being removed?

For example, if the lists are <code>[1,2,3,4,5]</code> and <code>[1,2,4,5]</code>, the function should return <code>3</code>

Which of the following methods would be the most efficient way of identifying what element is not included in two lists of integers that differ by a single element being removed? 

For example, if the lists are `[1,2,3,4,5]` and `[1,2,4,5]`, the function should return `3`

Efficiently Identifying Missing Integer

You’re given a string that may contain the characters <code>{</code>, <code>}</code>, <code>[</code>, <code>]</code>, <code>(</code>, and <code>)</code>.

Task: Verify that the string is balanced. A balanced string is one where every opening character, <code>{</code>, <code>[</code>, or <code>(</code>, has a corresponding closing character, <code>}</code>, <code>]</code>, or <code>)</code>.

Write a function called <code>is_balanced(string: str) -&gt; bool</code> which verifies the balance of a string.

Example:

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;(())[]{}&#39;) -&gt; True
</code></pre>

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;{([(){}])()}&#39;) -&gt; True
</code></pre>

<pre tabindex="0" class="chroma"><code>is_balanced(&#39;{}[]())&#39;) -&gt; False
</code></pre>

<hr/>

Let’s say that you’re the PM on Google Maps.

<ol>
<li>How would you improve Google Maps?</li>

<li>What metrics would you check to see if your feature improvements are successful?</li>
</ol>

Let’s say you are working at Facebook and are asked to investigate the claim that Facebook is losing young users.

<ol>
<li>How would you verify this claim?</li>
<li>What test metrics would you look at?</li>
</ol>

Let’s say you are working at Facebook and are asked to investigate the claim that Facebook is losing young users.

Pick the metric that is the least relevant for your analysis.

Let’s say you are working at Facebook and are asked to investigate the claim that Facebook is losing young users.

Pick the metric that is the least relevant for your analysis.

Given a <code>ListNode</code> representing the head of a linked list, write a function <code>is_cyclic</code> which returns <code>True</code> if a linked list is cyclic and <code>False</code> if it is not. A linked list is cyclic when there is no tail to the linked list, and the supposed tail is attached to another node inside the list itself, creating a cycle.

A <code>ListNode</code> is defined as:

<pre tabindex="0" class="chroma"><code>class ListNode:
	value: ListNode = None
 next: ListNode = None
</code></pre>

Example:

Input:

<img src="/s3/questions/1a65651d-a483-4481-b073-2738d65ab9d7.png" alt="image"/>

Output:

<pre tabindex="0" class="chroma"><code>def is_cyclic(head) -&gt; True
</code></pre>

Cyclic Detection

Why would the same machine learning algorithm generate different success rates using the same dataset?

Note: When they ask us an ambiguous question, we need to gather context and restate it in a way that’s clear for us to answer.

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years but found that around 20% of the listings are missing square footage data.

How do we deal with the missing data to construct our model?

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years, but have discovered that around 20% of the listings are missing square footage data.

How would you approach dealing with this missing data, in order to construct the most useful predictive model possible?

We want to build a model to predict housing prices in the city of Seattle. We’ve scraped 100K sold listings over the past three years, but have discovered that around 20% of the listings are missing square footage data.

How would you approach dealing with this missing data, in order to construct the most useful predictive model possible?



What are the key differences between classification models and regression models?

What is the MOST important difference between regression and classification models?

What is the MOST important difference between regression and classification models?

Classification vs Regression

Explain the key differences between classification models and regression models

Classification and Regression

An electronics retail company tracks its sales and wants to run a performance analysis. They’re hoping to categorize sales into different groups, based on the amount of sales and the region where the sale occurred. The conditions for categorization are:

<ul>
<li>Standard Sales: Any sales below 2000 are considered standard, except if they occur in the <code>East</code> region, or in the month of July.</li>
<li>Premium Sales: Any sales that are over or equal to 2000, or any sales in the <code>East</code> region (regardless of the amount), are considered premium, except again during the month of July.</li>
<li>Promotional Sales: All sales made in the promotional period of July, regardless of the amount or region, are considered promotional.</li>
</ul>

The company wants a report that sums these amounts by region to help with financial planning and bonus allocations.

Note: You may assume that table contains data only for 2023

Example:

Input:

<code>sales</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>sale_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>employee_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>product_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>sale_amount</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>sale_date</code></td>
<td>DATE</td>
</tr>

<tr>
<td><code>region</code></td>
<td>TEXT</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>region</code></td>
<td>TEXT</td>
</tr>

<tr>
<td><code>total_sales</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>premium_sales</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>standard_sales</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>promotional_sales</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>

Three zebras are chilling in the desert. Suddenly a lion attacks.
Each zebra is sitting on a corner of a triangle with sides of equal length.
Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?

Three zebras are chilling in the desert. Suddenly a lion attacks.

Each zebra is sitting on a corner of a triangle with side of equal length. Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?

Three zebras are chilling in the desert. Suddenly a lion attacks.

Each zebra is sitting on a corner of a triangle with side of equal length.  Each zebra randomly picks a direction and only runs along the outline of the triangle to either edge of the triangle.

What is the probability that none of the zebras collide?



Three Zebras

Brainteasers

Given two strings, write a function to return <code>True</code> if the strings are anagrams of each other and <code>False</code> if they are not.

Note: A word is not an anagram of itself.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>string_1 = &#34;listen&#34;
string_2 = &#34;silent&#34;
</code></pre>

Output:

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

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>string_1 = &#34;banana&#34;
string_2 = &#34;bandana&#34;
</code></pre>

Output:

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

The support team at your company is trying to analyze ticketing data to improve response times. They have noticed that a significant number of tickets have no assigned agent, making it difficult to track the progress of these tickets.

Write a SQL query to count the total number of tickets, the number of tickets assigned to agents, and the number of tickets that are not assigned to any agent.

Note: Tickets that are not assigned to any agent have <code>NULL</code> in their <code>agent_id</code> field.

Example:

Input:

<code>tickets</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td>id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>issue</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>agent_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>created_at</td>
<td>TIMESTAMP</td>
</tr>

<tr>
<td>updated_at</td>
<td>TIMESTAMP</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td>total_tickets</td>
<td>INTEGER</td>
</tr>

<tr>
<td>tickets_with_agent</td>
<td>INTEGER</td>
</tr>

<tr>
<td>tickets_without_agent</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

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>

What’s the difference between Lasso and Ridge Regression?

Under what circumstances is it recommended to use Lasso regression over Ridge regression?

Under what circumstances is it recommended to use Lasso regression over Ridge regression?

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?

Given a <code>users</code> table, write a query to return only its duplicate rows.

Example:

Input:

<code>users</code> table

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>

Let’s say that you work as a data scientist at a food delivery company.

You are tasked with building a model to predict food preparation times at a restaurant from the time when a customer sends in the order to when the meal is ready for the driver to pick up.

What are some reasons why measuring bias would be important in building this particular model?

What are some reasons why measuring bias would be important in building this particular model

Food Delivery Times

You’ve been tasked with building a classification machine-learning model to predict whether a transaction is either fraud or not fraud for a credit card company. You have ten years of historical data on transactions, including a flag for whether a transaction was manually identified as fraud.

Describe how you might go about building a fraud detection model for credit card transactions. Be sure to mention the possible model types, discuss the bias-variance tradeoff in model development, and address any complexities that arise from the class imbalance.

Input features in the data include:

<ul>
<li>Transaction amount</li>
<li>Merchant category for the transaction</li>
<li>Zip code for the merchant</li>
<li>Zip code for the billing address</li>
<li>Average transaction amount for the account over the past six months</li>
</ul>

Output feature:

<ul>
<li>0/1 flag for fraud (0 = not fraud, 1 = fraud)</li>
</ul>

Note: Fraudulent transactions are (thankfully) a very small percentage of all historical transactions. Assume fraudulent transactions are 0.01% of historical data.While building the model to perform the classification, you need to consider the bias/variance tradeoff, and take into account the fact that there is a class imbalance (very few of the observations are “fraud”).

Bias variance tradeoff and class imbalance in finance

Bias - Variance Tradeoff and Class Imbalance in Finance

Let’s say that we want to build a chatbot system for frequently asked questions. Whenever a user writes a question, we want to return the closest answer from a list of FAQs.

What are some machine learning methods for building this system?

Let’s say we’re designing a deep learning pipeline to process millions of customer support chat logs, and we want to use a Transformer encoder layer built in PyTorch to extract useful representations for downstream tasks like sentiment classification.

How would you approach building this Transformer encoder layer from scratch—what are the essential components, how would you implement them in PyTorch, and why are elements like residual connections and layer normalization critical for stable and effective training?

How would you build and justify the components of a Transformer encoder layer in PyTorch for large-scale text data?

Transformer Encoder Layer

AI & Agentic Systems

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

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

Suppose an array sorted in ascending order is rotated at some pivot unknown to you beforehand.

You are given a target value to search. If the value is in the array, then return its index; otherwise, return -1. 

Notes:

<ul>
<li>Rotating an array at pivot \(n\) gives you a new array that begins with the elements after position \(n\) and ends with the elements up to position \(n\).</li>
<li>You may assume no duplicate exists in the array.</li>
</ul>

Bonus: Your algorithm’s runtime complexity should be in the order of \(O(\log n)\).

Example:

Input: 

<pre tabindex="0" class="chroma"><code>sample_input = [0,1,2,4,5,6,7] 
rotated_input = [4,5,6,7,0,1,2]
target_value = 6
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def target_value_search(rotated_input, target_value) -&gt; 2
</code></pre>

Search for a value in log(n) over a sorted array that has been shifted.

Target Value Search

Let’s say we’ve proposed a new analytics dashboard to a client, but after reviewing our design and data sources, the client says the solution doesn’t meet their needs and pushes back on several key features.

How would you approach the conversation to negotiate alternative solutions, and what steps would you take to ensure disagreements are handled constructively so we can still reach a successful outcome?

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?

Bias vs. Variance Tradeoff

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

Addressing imbalanced data in machine learning through carefully prepared techniques.

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

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