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Machine Learning

Coefficients of Logistic Regression

Lasso vs Ridge

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

Softmax vs Logistic

Classification and Regression

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

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

Your Strengths and Weaknesses

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

Why Do You Want to Work With Us

Product Sense & Metrics

Unified Inbox

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

Fake News on Newsfeed

A/B Testing

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

Delivery Online

Statistics

P-value to a Layman

What are the assumptions of linear regression?

Assumptions of Linear Regression

Write a function to sample from a truncated normal distribution

Truncated Distribution

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

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

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>

Select the 2nd highest salary in the engineering department

2nd Highest Salary

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

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

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

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

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?

Declining Applicants

Business Case

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.

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

<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>

Get Top N Frequent Words

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

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?

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.

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 how the feature is performing?

Recruiting Leads

Analytics

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

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?

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 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

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

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

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 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

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

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?

Making data-driven insights actionable for those without technical expertise

Simple Explanations

Given a <code>percentile_threshold</code>, mean <code>m</code>, and standard deviation <code>sd</code> of the normal distribution, write a function <code>truncated_dist</code> to simulate a normal distribution truncated at <code>percentile_threshold</code>.

Example:

Input:

<pre tabindex="0" class="chroma"><code>m = 2
sd = 1
n = 6
percentile_threshold = 0.75
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def truncated_dist(m,sd,percentile_threshold): -&gt;

 [2, 1.1, 2.2, 3, 1.5, 1.3]
</code></pre>

All values in the output sample are in the lower 75% = <code>percentile_threshold</code> of the distribution.

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.

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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