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Cox Enterprises 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 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

Digit Accumulator

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

The Brackets Problem

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

Nearest Common Ancestor

Product Sense & Metrics

WAU vs Open Rates

Losing Users

Google Maps Improvement

Docs Metrics

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

Analyzing Churn Behavior

Machine Learning

Coefficients of Logistic Regression

Lasso vs Ridge

Bagging vs Boosting

FAQ Matching

Classification and Regression

Select the 2nd highest salary in the engineering department

2nd Highest Salary

Duplicate Rows

Time Difference

Total Time in Flight

Write a query that outputs a random manufacturer's name with an equal probability of selecting any name.

Uniform Car Maker

Data Pipelines

Design a data pipeline for hourly user analytics.

Data Pipelines and Aggregation

Design a solution to store and query raw data from Kafka on a daily basis.

Clickstream Data

Let's say that you're in charge of getting payment data into your internal data warehouse. 

Payment Data Pipeline

Describing a real-world data cleaning and organization project

Data Cleaning Experiences

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

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

Your Strengths and Weaknesses

Brainteasers

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

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

Why Do You Want to Work With Us

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

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

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

Write a SQL query to select the 2nd highest salary in the engineering department.

Note: If more than one person shares the highest salary, the query should select the next highest salary.

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>departments</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>
</tbody>
</table>
Output:

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

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

What is the difference between Logistic and Linear Regression?

When would use one instead of the other in practice?

What is the difference between Logistic and Linear Regression?

Linear vs Logistic Regression

Statistics

Tell me about a project in which you had to clean and organize a large dataset.

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

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>

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>

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 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

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/>

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>

How would you explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician? Ensure your explanations are tailored to the understanding level of each audience.

Describe linear regression to various audiences with different levels of knowledge.

Explaining Linear Regression to Different Audiences

Let’s say you have analytics data stored in a data lake. An analyst tells you they need hourly, daily, and weekly active user data for a dashboard that refreshes every hour.

How would you build this data pipeline?

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>

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

Pathfinder in Maze

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 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>

Describe an analytics experiment that you designed. How were you able to measure success?

The role of A/B testing in measuring the success rate of an analytics experiment

Success Measurement

A/B Testing

Let’s say that you’re in charge of getting payment data into your internal data warehouse.

How would you build an ETL pipeline to get Stripe payment data into the database so analysts can build revenue dashboards and run analytics?

Let’s say that you’re a data scientist on the engagement team. A product manager comes up to you and says that the weekly active users metric is up 5% but email notification open rates are down 2%.

What would you investigate to diagnose what’s happening?

Email Open Rate

Let’s say that you work for a company like Netflix. Netflix has two pricing plans: $15/month or $100/year.

Let’s say an executive at the company wants you to analyze the churn behavior of users that subscribe to either plan.

What kinds of metrics / graphs / models would you build to help give the executive an over-arching view of how the subscriptions are performing?

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?

You’re a data scientist for Instagram’s product team.

A product manager proposes changing the platform’s messaging system to allow interactions with other platforms and third-party businesses.

For example, Instagram could partner with GrubHub to allow the company to send messages to Instagram users about their GrubHub order.

Question: How would you determine whether this change is a good idea?

Unified Inbox

Business Case

Let’s say that you’re in charge of Square’s small business division. 

The CEO wants to hire a customer success manager to help manage a new software product. Another executive thinks that it’s worth just instituting a free trial instead.

What would be your recommendation on utilizing a customer success manager versus just a free trial to get new or existing customers to use the new product?

Customer Success vs. Free Trial

Challenge

Cox Enterprises Salaries by Position

* Engages with business partners or departments across the business or even outside of Ready to: + Define analytical needs, shape problem statements, and design high?impact analytical frameworks that guide strategic decision?making. + Lead complex analyses across multiple data sources, evaluating trends, diagnosing root causes, and synthesizing findings into actionable insights that influence business performance and direction. This includes analyzing current and historical business data, assessing trends, and identifying and explaining variance from goals as well as providing recommendations + Establish and oversee key performance metrics, ensuring they accurately reflect business objectives and are grounded in sound analytical methodology. + Distill large data sets down to a set of meaningful and actionable insights with minimal direction or criteria + Apply expert?level analytical capabilitiesincluding regression, predictive modeling, or automated workflowsto evaluate business scenarios and develop forward?looking recommendations. + Conduct strategic ad?hoc analyses, defining hypotheses, selecting methodologies, designing datasets, and delivering insights that shape policy, process, or operational direction. + Ensure timely and accurate delivery of reports + Design, develop, and manage sophisticated reporting and dashboards, applying advanced analytical techniques and ensuring reliability, scalability, and meaningful data storytelling.* Utilizes more advanced methodologies or analytical/reporting capabilities beyond descriptive statistics, for example, may have experience building regressions or predictive models or may have built automated reporting workflows* Demonstrates strong to expert knowledge of technical, process, and business principles, industry practices, and standards. Considered a subject matter expert.* Serves as a subject matter expert and thought partner, guiding cross?functional teams, advising stakeholders, and elevating analytical maturity across the organization. Supports multiple areas of the business and may even partner with business units that are adjacent or outside of Ready (Operations, Verification, BPO, Client Success; Central Dispatch and Manheim, etc). Challenge leadership assumptions when data contradicts strategy* Effectively applies functional, process, procedural or technical imagination to address business challenges and uses innovative solutions to enhance personal work* Leads the diagnosis and resolution of complex data, metric, and reporting issues, independently determining corrective actions and driving sustainable, organization?wide solutions. Independently identifies and pursues high-value analytical opportunities.* Conducts ad-hoc analysis as requested or upon noticing changes to trends in a self-directed manner to assess things like savings opportunities or recommendations for optimization opportunities* Drives data governance efforts by establishing and refining metric definitions, championing standardization, and ensuring consistency and accuracy across all reporting environments. Maintains and improves metric definitions and reporting logic, proactively identifying inconsistencies and initiating governance updates to strengthen data accuracy and alignment.* Determines when to escalate vs. resolve issues independently* Understands broader issues outside own discipline, considers multiple job areas or specialties, and draws from prior experience to solve problems.* Collaborates cross-functionally to evaluate technical, system and process improvements.* Performs assignments with limited supervision, receiving guidance only on unusual or complex problems / issues when requested.* Coaches and mentors analysts at all levels, promoting analytical rigor, structured thinking, and continuous improvement within the broader analytics function.Minimum Qualifications**:*** BA/BS degree and 4+years of experience OR equivalent combination of education and experience (MS/MA and 2+ yrs experience | PHD and 1 yr experience) OR 8 years of experience with HS Diploma* Advanced skills with excel* Skilled using reporting tools like Tableau or PowerBI to design reports or conduct analysis* Preferred. Experience using Snowflake, SQL, or Python to gather, analyze, and report on dataCox brings together the worlds greatest minds to help breathe life into new possibilities and drive innovation for a better future. Thats why we look for individuals who share our pioneering spirit, have imaginative ideas and are fearless when it comes to tackling the worlds biggest challenges. Our people love technology and they love making a difference. They have a passion for finding new solutions and working with brilliant colleagues. Every day they dedicate themselves to a huge range of exciting projects, contributing to the Cox vision around the globe. From engineering new sustainability solutions that conserve water and energy to creating the infrastructure for the smart cities of tomorrow, theres no challenge too great for our pioneers. And theres no shortage of opportunities for you to make a difference. Come and experience the dynamic, collaborative and creative environments where your ideas are welcome and new discoveries are waiting. To help you grow to your full potential, we strive to support our employees in their career aspirations and promote the freedom to explore new horizons. #J-18808-Ljbffr

<h5>Lead Data Engineer </h5>The Lead Data Engineer is responsible for processing structured and unstructured data, validating data quality, and developing and supporting data products. The Senior Data Engineer also plays a role in Agile planning, providing advice and guidance, and monitoring emerging technologies. WHAT YOU'LL DO Key Responsibilities: <ul> <li>Process structured and unstructured data <ul> <li>Gathers and processes raw, structured, semi-structured, and unstructured data using batch and real-time data processing frameworks. </li> <li>Understands and enforces appropriate data master management techniques. </li> </ul></li> <li>Data validation and quality <ul> <li>Ensures data quality and implements tools and frameworks for automating the identification of data quality issues. </li> <li>Work with internal and external data providers on data validation providing feedback and making customized changes to data feeds and data mappings. </li> </ul></li> <li>Agile planning <ul> <li>Understands the challenges that the analytics organization faces in their day-to-day work and partner with them to design viable data solutions. </li> <li>Recommends improvements to processes, technology, and interfaces that improve the effectiveness of the team and reduce technical debt. </li> </ul></li> <li>Product development <ul> <li>Implements and optimizes data solutions in enterprise data warehouses and big data repositories. </li> <li>Installs, maintains, monitors, and supports business intelligence, distributed computation, and big data analytics tools. </li> </ul></li> <li>Application support <ul> <li>Provides ongoing support, monitoring, and maintenance of deployed products. </li> </ul></li> <li>Advice and guidance <ul> <li>Actively works with less experienced data engineers providing technical guidance and oversight. </li> </ul></li> <li>Emerging technology monitoring <ul> <li>Actively participates in the engineering community, staying up to date on new data technologies and best practices and shares insights with others in the organization. </li> </ul></li> </ul>Who You Are Qualifications: <ul> <li>Applicants must currently be authorized to work in the United States for any employer without current or future sponsorship. No OPT, CPT, STEM/OPT or visa sponsorship now or in future. </li> <li>Must live within a commutable distance to Atlanta GA </li> <li>Bachelor's degree in Computer Science or related field and 6+ years experience OR Masters Degree w/ 4+ years experience OR 18 years experience of equivalent combination of industry related professional experience and education. </li> <li>Must have 4+ years professional experience working as a Data Engineer </li> <li>Working experience with batch and real-time data processing frameworks </li> <li>Strong working experience with data modelling, data access, schemas, and data storage techniques within Snowflake </li> <li>Working experience in design, development, and implementation of highly scalable, high-volume software systems and components, client-facing web applications, and major Internet-oriented applications and systems </li> <li>Working experience with relational databases such as SQL, MySQL, Postgres/PostgreSQL </li> <li>Working experience with business intelligence tools and platforms </li> <li>Working experience with data quality tools </li> <li>Working experience with application lifecycle methodologies (e.g. waterfall, agile, iterative) </li> <li>Experience with ETL processes and tools </li> <li>Experience working with Git </li> <li>Experience or exposure to DBT </li> <li>Experience working with AI related tools such as co-pilot </li> <li>Experience implementing new tools into environments </li> </ul>Preferred Qualifications: <ul> <li>Scrum Developer Certification or equivalent </li> <li>Working experience with Sisense platform </li> <li>Working experience with SQL Server Integration Services </li> <li>Working experience with AWS data tools (Database Migration Service) </li> <li>Working experience with Python </li> <li>Experience working with Jira, Rally or similar tools </li> </ul>Drug Testing To be employed in this role, you'll need to clear a pre-employment drug test. Cox Automotive does not currently administer a pre-employment drug test for marijuana for this position. However, we are a drug-free workplace, so the possession, use or being under the influence of drugs illegal under federal or state law during work hours, on company property and/or in company vehicles is prohibited. Benefits The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave. About Us Through groundbreaking technology and a commitment to stellar experiences for drivers and dealers alike, Cox Automotive employees are transforming the way the world buys, owns, sells or simply uses cars. Cox Automotive employees get to work on iconic consumer brands like Autotrader and Kelley Blue Book and industry-leading dealer-facing companies like vAuto and Manheim, all while enjoying the people-centered atmosphere that is central to our life at Cox. Benefits of working at Cox may include health care insurance (medical, dental, vision), retirement planning (401(k)), and paid days off (sick leave, parental leave, flexible vacation/wellness days, and/or PTO). For more details on what benefits you may be offered, visit our benefits page. Cox is an Equal Employment Opportunity employer All qualified applicants/employees will receive consideration for employment without regard to that individual's age, race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender, gender identity, physical or mental disability, veteran status, genetic information, ethnicity, citizenship, or any other characteristic protected by law. Cox provides reasonable accommodations when requested by a qualified applicant or employee with disability, unless such accommodations would cause an undue hardship.

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

Cox Enterprises Interview Questions

Cox Enterprises Interview Guides