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Saildrone Inc Interview Questions

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Data Structures & Algorithms

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

Prime to N

Given a string, write a function to find its first recurring character.

Recurring Character

Reconstruct the path of a trip so that the trip tickets are in order.

Scrambled Tickets

Write a function `sort_lists` to combine sorted integer lists into one sorted list without using libraries or `sort`/`sorted`

Merge N Sorted Lists

Implementing a priority queue used linked lists.

Priority Queue Using Linked List

Machine Learning

How would we build a model to detect fraud and text customers to approve or deny fraudulent transactions

Bank Fraud Model

Lasso vs Ridge

Rebalancing outcome probabilities for a classifier on imbalanced data.

Rebalance Probabilities

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

Bagging vs Boosting

What kind of model did the co-worker develop, how would you measure the difference between the two credit risk models within a timeframe, and what metrics would you track to measure the success of the new model

Loan Model

Behavioral

Describing a data project and its challenges

Hurdles In Data Projects

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

How to present complex data insights with clarity and adaptability tailored to a specific audience

Presentations and Insights

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

Analytics

How would you present the performance of each subscription to an executive?

Analyzing Churn Behavior

How would you approach improving the quality of airline data?

Addressing Data Quality Issues

Which metric should we use for late orders if the distribution is right-skewed and what does that tell us?

Late Orders

Let's say you work at Facebook and you're analyzing churn on the platform.

Retention Rate Disparity

You’re tasked with analyzing data from multiple sources, such as payment transactions, user behavior, and fraud detection logs. How would you approach solving a data analytics problem involving these diverse datasets? What steps would you take to clean, combine, and extract meaningful insights that could improve the system's performance?

Analyzing Multiple Data Sources

Business Case

How would you evaluate and choose between a fast, simple model and a slower, more accurate one for product recommendations?

Deciding Between Solutions

How would you evaluate switching to a new vendor offering better terms after signing a long-term contract?

Alternative Vendor Tradeoff

As a data scientist at a mortgage bank, how would you approach building a predictive model for loan default risk?

Risk Model for a Mortgage Bank

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>

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?

Over budget on a project is defined when the salaries, prorated to the day, exceed the budget of the project.

For example, if Alice and Bob both combined income make 200K and work on a project of a budget of 50K that takes half a year, then the project is over budget given 0.5 * 200K = 100K &gt; 50K.

Write a query to forecast the budget for all projects and return a label of <code>&#34;overbudget&#34;</code> if it is over budget and <code>&#34;within budget&#34;</code> otherwise.

Note: Assume that employees only work on one project at a time.

Example:

Input:

<code>employees</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>first_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>last_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>salary</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>department_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>projects</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>title</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>state_date</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>end_date</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>budget</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
departments 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>
</tbody>
</table>
<code>employee_projects</code> table

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

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

<tr>
<td><code>employee_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

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

<tbody>
<tr>
<td><code>title</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>project_forecast</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>

Write a query to forecast each project's budget and label it overbudget or within budget

Over-Budget Projects

Given a string, write a function <code>recurring_char</code> to find its first recurring character. Return <code>None</code> if there is no recurring character.

Treat upper and lower case letters as distinct characters.

You may assume the input string includes no spaces.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>input = &#34;interviewquery&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>output = &#34;i&#34;
</code></pre>

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>input = &#34;interv&#34;
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>output = None
</code></pre>

Consider a trip from one city to another that may contain many layovers. Given the list of flights out of order, each with a starting city and end city, write a function <code>plan_trip</code> to reconstruct the path of the trip so the trip tickets are in order.

Example:

For a trip from Bombay to Beijing:

Input:

<pre tabindex="0" class="chroma"><code>flights = [
 [&#39;Chennai&#39;, &#39;Bangalore&#39;], 
 [&#39;Bombay&#39;, &#39;Delhi&#39;], 
 [&#39;Goa&#39;, &#39;Chennai&#39;], 
 [&#39;Delhi&#39;, &#39;Goa&#39;], 
 [&#39;Bangalore&#39;, &#39;Beijing&#39;]
]
output = [
 [&#39;Bombay&#39;, &#39;Delhi&#39;], 
 [&#39;Delhi&#39;, &#39;Goa&#39;], 
 [&#39;Goa&#39;, &#39;Chennai&#39;], 
 [&#39;Chennai&#39;, &#39;Bangalore&#39;], 
 [&#39;Bangalore&#39;, &#39;Beijing&#39;],
]
</code></pre>

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?

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

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/>

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

The Brackets Problem

What is the difference between covariance and correlation? Provide an example.

Explain the difference between covariance and correlation and provide an example

Covariance vs Correlation

Statistics

How does random forest generate the forest? Additionally, why would we use it over other algorithms such as logistic regression?

What happens when you average the output on multiple decision trees?

What happens when you average the output on multiple decision trees?

Average Trees

How does random forest generate the forest and why use it over logistic regression

Random Forest Explanation

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?

Priority queues are an abstract data structure responsible for allowing enqueuing items with an attached priority. While typically implemented with a heap, implement a priority queue using a linked list.

The Priority Queue implementation should support the following operations:

<ul>
<li><code>insert</code>(element, priority): This operation should be able to insert an element into the Priority Queue, along with its corresponding priority.</li>
<li><code>delete()</code>: This operation should remove and return the element with the highest priority. If multiple elements share the same highest priority, the element first enqueued should be returned. In the case that the queue is empty, return None.</li>
<li><code>peek()</code>: This operation should return the element with the highest priority without removing it from the Priority Queue. Again, in the case of equal highest priorities, the element first enqueued should be returned. In the case that the queue is empty, return None.</li>
</ul>

Note: Smaller priority values imply that they have higher priority.

<h3>Input</h3>

<pre tabindex="0" class="chroma"><code>queue.insert(2, 1)
queue.insert(3, 3)
</code></pre>

<h3>Output:</h3>

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

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

Given a list of sorted integer lists, write a function <code>sort_lists</code> to create a combined list while maintaining sorted order without importing any libraries or using the <code>&#39;sort&#39;</code> or <code>&#39;sorted&#39;</code> functions in Python.

Example:

Input:

<pre tabindex="0" class="chroma"><code>lists = [
[1,2,3,4,5,6],
[2,5,7,8],
[3,9,10,12],
[0,1,2,8]
]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def sort_lists(lists) -&gt; [0,1,1,2,2,3,3,4,5,5,6,7,8,8,9,10,12]
</code></pre>

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

Every night between 7 pm and midnight, two computing jobs from two different sources are randomly started with each one lasting an hour.

Unfortunately, when the jobs simultaneously run, they cause a failure in some of the company’s other nightly jobs, resulting in downtime for the company that costs $1000. 

The CEO, who has enough time today to hear one word, needs a single number representing the annual (365 days) cost of this problem.

Note: Write a function to simulate this problem and output an estimated cost 

Bonus - How would you solve this using probability?

Example:

Input:

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

Output:

<pre tabindex="0" class="chroma"><code>simulate_overlap(n) -&gt; 0.4
</code></pre>

Find how much overlapping jobs are costing the company

Nightly Job

Probability

Let’s say you work for a bank that gives out personal loans. Your co-worker develops a model that takes in customer inputs and returns if a loan should be given or not.

<ol>
<li>What kind of model did the co-worker develop? 
</li>
<li>Another co-worker thinks they have developed a better model to predict defaults on the loans. Given that personal loans are monthly installments of payments, how would you measure the difference between the two credit risk models within a timeframe? 
</li>
<li>What metrics would you track to measure the success of the new model?</li>
</ol>

You are given an array of strings <code>arr</code>, where each string is in the format: <code>&lt;letters&gt;&lt;number&gt;</code>. For example, you might see <code>&#34;a1&#34;</code>, <code>&#34;b32&#34;</code>, or <code>&#34;caba522&#34;</code>.

Write a function called <code>custom_sort(arr)</code>, which sorts the list of strings in two ways: first by the letter, in alphabetical order, and second by the numbers in descending order.

Note: The letters can only be lower case, and have length $≥1$.

Example:

Input:

<pre tabindex="0" class="chroma"><code>arr = [&#34;b12&#34;, &#34;a15&#34;, &#34;b7&#34;, &#34;a3&#34;, &#34;c4&#34;, &#34;c20&#34;]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>custom_sort(arr) -&gt; &#39;[&#34;a15&#34;, &#34;a3&#34;, &#34;b12&#34;, &#34;b7&#34;, &#34;c20&#34;, &#34;c4&#34;]&#39;
</code></pre>

Implement a merge sort on an array of alphanumeric strings, sorting by letters alphabetically and numbers in descending order

Descending Alphanumeric Sorting

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

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.

Data Preparation for Imbalanced Data

How would you tackle multicollinearity in multiple linear regression?

How would you tackle multicollinearity in multiple linear regression

Multicollinearity in Regression

Let’s say we’re building a recommendation system for an e-commerce site, and we have two viable approaches: a collaborative filtering model that takes 2 days to implement, and a deep learning model that could boost accuracy by 10% but requires 3 weeks of engineering time.

How would you decide which solution to pursue, and what factors would you weigh in your decision?

Imagine you run a pizza franchise, and you run into a problem with a lot of no-shows after customers place their order.

What features would you include in a model to try to predict a no-show?

What features would you include in a model to predict a no-show

Pizza No Show

You have been tasked with designing three classes: <code>text_editor</code>, <code>moving_text_editor</code>, and <code>smart_text_editor</code>. These classes are to be created with specific functionalities as defined below:

<ol>
<li><code>text_editor</code> class:

<ul>
<li><code>write_line(string:str)</code>: A method which appends a given string to the end of the existing string.</li>
<li><code>delete_line(char_num : int)</code>: A method which deletes <code>char_num</code> number of characters from the existing string, starting from the end. If there are no characters left, the method should do nothing.</li>
<li><code>special_operation()</code>: A method which currently does nothing.</li>
<li><code>get_notes()</code>: A method which returns the internal string.</li>
</ul></li>

<li><code>moving_text_editor</code> class:

<ul>
<li>This class extends <code>text_editor</code>. The <code>special_operation()</code> method is overridden. Initially, the cursor will be at the end of the current string. If <code>special_operation()</code> is called, it moves the cursor to the beginning of the string, any additional appends will be appended to the beginning of the string instead. Calling <code>special_operation()</code> again reverses the cursor operation.</li>
</ul></li>

<li><code>smart_text_editor</code> class:

<ul>
<li>This class extends <code>text_editor</code>. In this class, the <code>special_operation()</code> method is overridden to serve as an undo operation, allowing it to undo an infinite number of operations.</li>
</ul></li>
</ol>

<h3>Input</h3>

<pre tabindex="0" class="chroma"><code>[[&#39;special_text_editor&#39;], [&#39;write_line&#39;, &#39;special_operation&#39;, &#39;write_line&#39;], [&#39;World&#39;, &#39;Hello, &#39;]]
</code></pre>

<h3>Output</h3>

<code>&#34;Hello, World&#34;</code>

Create a text editor while displaying method overriding as a concept.

Text Editor With OOP

Design Patterns

Let’s say you’re working with a dataset of user-level events for a new product feature, and you notice issues like missing values, duplicate records, inconsistent data types, and some clear outliers. You need to prepare this data for training a machine learning model.

How would you design a data processing pipeline using Pandas and NumPy to clean and validate the data before modeling, and what steps would you take to ensure the pipeline is reusable and reliable for future use?

How would you build a reusable data cleaning pipeline for messy user event data?

User Event Data Pipeline

Data Pipelines

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

Given an (integer) height <code>h</code> and base <code>b</code>, write a function <code>draw_isosceles_triangle</code> that returns the shape of the isosceles triangle using (a 2D list) of <code>0</code>s and <code>1</code>s, where <code>0</code> and <code>1</code> represent the space outside and inside of the triangle, respectively.

If the given height <code>h</code> and base <code>b</code> cannot make a triangle, return <code>None</code>.

Note: Valid arguments for <code>b</code> should be odd

Example 1

Input:

<pre tabindex="0" class="chroma"><code>h = 2
b = 3
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>draw_isosceles_triangle(h,b) -&gt; [
 [0,1,0],
 [1,1,1]
]
</code></pre>

Example 2

Input:

<pre tabindex="0" class="chroma"><code>h = 3
b = 9
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>draw_isosceles_triangle(h,b) -&gt; [
 [0,0,0,0,1,0,0,0,0],
 [0,0,1,1,1,1,1,0,0],
 [1,1,1,1,1,1,1,1,1]
]
</code></pre>

Example 3

Input:

<pre tabindex="0" class="chroma"><code>h = 5
b = 9
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>draw_isosceles_triangle(h,b) -&gt; [
 [0,0,0,0,1,0,0,0,0],
 [0,0,0,1,1,1,0,0,0],
 [0,0,1,1,1,1,1,0,0],
 [0,1,1,1,1,1,1,1,0],
 [1,1,1,1,1,1,1,1,1] 
]
</code></pre>

Example 4

Input:

<pre tabindex="0" class="chroma"><code>h = 9
b = 9
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>draw_isosceles_triangle(h,b) -&gt; None
</code></pre>

Write a function that returns the shape of an isosceles triangle.

Triangle as Binary Array

Let’s say we’ve built a neural network for image classification using NumPy, and we’re training it in a distributed environment with several workers. We notice that, even when using the same random seed, the loss curve looks erratic across different training runs, model weights diverge between workers, and training results aren’t consistent between single-node and distributed setups.

How would you go about diagnosing and resolving these distributed training inconsistencies to ensure stable and reproducible results?

How would you debug and fix inconsistencies in distributed NumPy neural network training?

Distributed Training Instability

Concurrent & Distributed Systems

You work as a software engineer at Credit Karma. The team is tasked with building a backend API that retrieves and serves relevant financial product offers, such as credit cards, personal loans, and auto loans, based on user profiles.

When a user logs in, the API must fetch all available offers from multiple partner services, filter them using factors like credit score, and return only the most relevant auto loan offers if the user expresses interest.

How would you architect the API endpoints and backend logic to support this functionality?

Design a backend API for serving filtered, relevant financial offers based on user profiles.

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

Saildrone Inc Interview Questions

Saildrone Inc Interview Guides

Saildrone Inc Interview Questions

Challenge

Discussion & Interview Experiences

Discussion & Interview Experiences