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Machine Learning

Interpret coefficients of logistic regression for categorical and boolean variables

Coefficients of Logistic Regression

Lasso vs Ridge

What are the logistic and softmax functions? What is the difference between the two?

Softmax vs Logistic

Explain the key differences between classification models and regression models

Classification and Regression

How will two highly correlated features appear in a random forest feature importance measurement

Correlated Features in Forests

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

Why Do You Want to Work With Us

Making data-driven insights actionable for those without technical expertise

Simple Explanations

Product Sense & Metrics

Unified Inbox

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

Docs Metrics

Pitching a feature idea that could drive success for Instagram Stories

Boosting Instagram Stories

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

Success Measurement

Design a system to detect and filter fake news in a social network newsfeed

Fake News on Newsfeed

A/B Testing

How would you determine if the new model predicts delivery times better than the old model

Delivery Estimate Model

Button AB Test

Precisely ascertain whether the outcomes of an A/B test, executed to assess the impact of a landing page redesign, exhibit statistical significance.

Statistically Significant Test

How would you test whether the feature was working successfully

Delivery Online

Select the 2nd highest salary in the engineering department

2nd Highest Salary

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

International e-Commerce Warehouse

Write a SQL query to compute the total revenue for each (season, year) pair by joining two tables on multiple columns.

Seasonal Product Performance Analysis

Explain the difference between the XGBoost and random forest algorithms and give an example where you would use one over the other.

Why might a data scientist choose to use XGBoost instead of Random Forest for a particular machine learning task?

Why might a data scientist choose to use XGBoost instead of Random Forest for a particular machine learning task?

XGBoost vs Random Forest: Choice

Explain the difference between XGBoost and random forest and give an example where you would use one over the other

Xgboost vs Random Forest

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>

How would you explain what a p-value is to someone who is not technical?

What does a p-value in a statistical test represent?

What does a p-value in a statistical test represent?

P-value to a Layman I

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

P-value to a Layman II

Explain what a p-value is to someone who is not technical

P-value to a Layman

Statistics

A team wants to A/B test multiple different changes through a sign-up funnel.

For example, on a page, a button is currently red and at the top of the page. They want to see if changing a button from red to blue and/or from the top of the page to the bottom of the page will increase click-through.

How would you set up this test?

Your team wants to run an AB test on the color (red or blue) and position (top/bottom of the page) of a button that links to a promotion.

How many different variants of the test should you run to see the effect that a red button has on the bottom of the page, if currently the button is blue and on the top of the page.

Your team wants to run an AB test on the color (red or blue) and position (top/bottom of the page) of a button that links to a promotion.

How many different variants of the test should you run to see the effect that a red button has on the bottom of the page, if currently the button is blue and on the top of the page.

A/B Test Variants

Let’s say we want to build a new delivery time estimate model for consumers ordering food delivery.

How would you determine if the new model predicts delivery times better than the old model?

When rolling out a new delivery time estimate model in production, what is an important consideration?

When rolling out a new delivery time estimate model in production, what is an important consideration?

Delivery Estimate Model I

What is one way to measure the performance of a new delivery time estimate model for food delivery?

What is one way to measure the performance of a new delivery time estimate model for food delivery?

Delivery Estimate Model II

Given a sorted list of positive integers with some entries being <code>None</code>, write a function to return a new list where all <code>None</code> values are replaced with the most recent non-<code>None</code> value in the list.

Note: If the first entry in the list is <code>None</code>, assume the previous entry was <code>0</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>input_list = [1,2,None,None,4,5,None]
</code></pre>

Output:

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

Write a function to return a new list where all empty values are replaced with the most recent non-empty value in the list.

Fill None Values

Data Structures & Algorithms

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?

<ol>
<li>Given an example paragraph string and an integer <code>N</code>, write a function <code>n_frequent_words</code> that returns the top <code>N</code> frequent words in the posting and the frequencies for each word.</li>

<li>What’s the function run-time?</li>
</ol>

Example:

Input:

<pre tabindex="0" class="chroma"><code>posting = &#34;&#34;&#34;
Herbal sauna uses the healing properties of herbs in combination with distilled water. 
The water evaporates and distributes the effect of the herbs throughout the room. 
A visit to the herbal sauna can cause real miracles, especially for colds. 
&#34;&#34;&#34; 
n = 3
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>n_frequent_words(posting,N) = [
 (&#39;the&#39;, 6), 
 (&#39;herbal&#39;, 2), 
 (&#39;sauna&#39;, 2),
]
</code></pre>

Write a function n_frequent_words that returns the top N frequent words and their frequencies, and state its run-time

Get Top N Frequent Words

Let’s say that you’re looking at the metrics of a job board. You see that the number of job postings per day has more or less remained the same the last few months but the number of applicants that have applied to jobs has steadily been decreasing.

Why would this be happening?

Why would the number of applicants be steadily decreasing while job postings remain the same

Declining Applicants

Business Case

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

What are the assumptions of linear regression?

Assumptions of Linear Regression

Walmart is analyzing how product performance changes across American seasons: Spring, Summer, Fall, Winter. The company stores sales records and seasonal product assignments in separate tables. A product may belong to different seasonal collections in different years.

Write a SQL query to compute the total revenue for each (season, year) pair by joining the two tables on multiple columns. Your final output should include <code>season</code>, <code>year</code> and <code>total_revenue</code> (rounded to 2 decimals)

Sort results by <code>year</code> ascending, then by season order: Spring → Summer → Fall → Winter.

Notes

<ul>
<li>The join must match on <code>product_id</code> AND <code>year</code>.</li>
<li>Seasonal assignment varies by year.</li>
<li>Revenue is computed from: <code>quantity * price</code></li>
<li>Every season/year combination appearing in the data must be included.</li>
</ul>

Schema

Input

<code>seasonal_products</code> table

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

<tbody>
<tr>
<td>product_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>season</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>year</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<code>sales</code> table

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

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

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

<tr>
<td>year</td>
<td>INTEGER</td>
</tr>

<tr>
<td>quantity</td>
<td>INTEGER</td>
</tr>

<tr>
<td>price</td>
<td>DECIMAL</td>
</tr>
</tbody>
</table>
Output

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

<tbody>
<tr>
<td>season</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>year</td>
<td>INTEGER</td>
</tr>

<tr>
<td>total_revenue</td>
<td>DECIMAL</td>
</tr>
</tbody>
</table>
Example

Input

<code>seasonal_products</code> table

<table>
<thead>
<tr>
<th>product_id</th>
<th>season</th>
<th>year</th>
</tr>
</thead>

<tbody>
<tr>
<td>10</td>
<td>Spring</td>
<td>2024</td>
</tr>

<tr>
<td>10</td>
<td>Summer</td>
<td>2024</td>
</tr>

<tr>
<td>20</td>
<td>Fall</td>
<td>2024</td>
</tr>

<tr>
<td>30</td>
<td>Winter</td>
<td>2024</td>
</tr>
</tbody>
</table>
<code>sales</code> table

<table>
<thead>
<tr>
<th>sale_id</th>
<th>product_id</th>
<th>year</th>
<th>quantity</th>
<th>price</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>10</td>
<td>2024</td>
<td>2</td>
<td>50</td>
</tr>

<tr>
<td>2</td>
<td>10</td>
<td>2024</td>
<td>1</td>
<td>40</td>
</tr>

<tr>
<td>3</td>
<td>20</td>
<td>2024</td>
<td>3</td>
<td>30</td>
</tr>

<tr>
<td>4</td>
<td>30</td>
<td>2024</td>
<td>1</td>
<td>100</td>
</tr>
</tbody>
</table>
Output

<table>
<thead>
<tr>
<th>season</th>
<th>year</th>
<th>total_revenue</th>
</tr>
</thead>

<tbody>
<tr>
<td>Spring</td>
<td>2024</td>
<td>140.00</td>
</tr>

<tr>
<td>Summer</td>
<td>2024</td>
<td>140.00</td>
</tr>

<tr>
<td>Fall</td>
<td>2024</td>
<td>90.00</td>
</tr>

<tr>
<td>Winter</td>
<td>2024</td>
<td>100.00</td>
</tr>
</tbody>
</table>
Explanation

In Spring 2024, product 10 appears with total sales of (2 × 50) + (1 × 40) = 140. In Summer 2024, the same product is assigned to a different season within the same year, so its total is again 140. In Fall 2024, only product 20 appears, giving 3 × 30 = 90. In Winter 2024, only product 30 appears with 1 × 100 = 100.

The key detail:

A product may appear in multiple seasons in the same year, but JOIN must match both the product_id and year, ensuring that seasonal assignment is year-specific.

Let’s say you’re a data scientist at LinkedIn where you’re working on a product that sends qualified job candidates to companies. The team has launched a new feature that allows candidates to message hiring managers at companies directly during the interview process to get updates on their status.

Due to engineering constraints, the company can’t AB test the feature before launching it.

How would you analyze how the feature is performing?

How would you analyze the performance of a new LinkedIn feature that lets candidates message hiring managers during the interview process

Recruiting Leads

Analytics

You’re a data scientist at YouTube. Leadership wants to revisit how the platform measures success, not for a specific new feature, but for the product as a whole given its current state.

How would you define and measure success for YouTube? Identify your primary and secondary metrics, explain your rationale for each, and discuss how you would choose the right thresholds for any engagement-based metrics you propose.

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?

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?

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

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

Write a function to simulate drawing balls from a jar. The colors of the balls are stored in a list named <code>jar</code>, with corresponding counts of the balls stored in the same index in a list called <code>n_balls</code>.

Example: 

Input:

<pre tabindex="0" class="chroma"><code>jar = [&#39;green&#39;, &#39;red&#39;, &#39;blue&#39;]
n_balls = [1, 10, 2]
# 1 green ball
# 10 red balls
# and 2 blue balls
</code></pre>

Output

<pre tabindex="0" class="chroma"><code>sample_multinomial(jar, n_balls) -&gt; &#34;blue&#34;
</code></pre>

Write code to generate a sample from a multinomial distribution with keys 

Drawing Balls From Bin

Probability

What are the logistic and softmax functions? What is the difference between the two?

What makes them useful for use in logistic regression?

In logistic regression, how is the predicted class determined based on the logistic function?

In logistic regression, how is the predicted class determined based on the logistic function?

Softmax vs Logistic II

What is the key characteristic of the logistic function that makes it useful for mapping continuous values to a probability?

What is the key characteristic of the logistic function that makes it useful for mapping continuous values to a probability?

Softmax vs Logistic I

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

Let’s say that you’re training a classification model.

How would you combat overfitting when building tree-based models?

Let's say that you're training a classification model.   How would you combat overfitting when building tree-based models?

Overfit Avoidance

Imagine you are designing a database for Etsy.
How would you distinguish between sharding and partitioning, and why might you choose one approach over the other?

Explain the differences and decision factors between sharding and partitioning in databases.

Sharding vs Partitioning

Big Data

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

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

Let’s say our company currently sources 80% of its electronics components from factories in China, but a new 50% tariff on Chinese imports is about to take effect.

How would you approach re-designing our supply chain to minimize costs, and what steps would you take to estimate the resulting financial impact?

How would you redesign the supply chain and estimate financial impact after a major China tariff?

China Tariff Supply Chain

Supply Chain

Let’s say you’re building an interactive Tableau dashboard for Fabletics’ merchandising team to help them monitor weekly sales performance across different product categories and regions.

How would you explain the difference between filters and parameters in Tableau to a non-technical stakeholder, and in what kinds of scenarios would you recommend using each one on this dashboard?

How would you explain and apply filters versus parameters on a Fabletics sales dashboard?

Tableau Filters and Parameters

Data Viz & Interpretation

Let’s say you work for an e-commerce company. Vendors can send products to the company’s warehouse to be listed on the website. Users are able to order any in-stock products and submit returns for refunds if they’re not satisfied.

The front end of the website includes a vendor portal that provides sales data in daily, weekly, monthly, quarterly, and yearly intervals.

The company wants to expand worldwide. They put you in charge of designing its end-to-end architecture, so you need to know what significant factors you’ll need to consider. What clarifying questions would you ask?

What kind of end-to-end architecture would you design for this company (both for ETL and reporting)?

Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?

You’re a product manager at Meta. In a few weeks, there is an upcoming stakeholder meeting, and they want you to suggest a new feature for Instagram Stories. What would this feature be, and what would be the rationale behind choosing such a feature?

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

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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