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Centrifuge Inc Interview Questions

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Machine Learning

Credit Card Fraud Model

Implement gradient descent to calculate the parameters of a line of best fit

Gradient Descent Calculation

Implement logistic regression from scratch in code

Logistic Regression from Scratch

Behavioral

Describing a data project and its challenges

Hurdles In Data Projects

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

Data Structures & Algorithms

Implement a dynamic recursive fibonacci function.

Impossibly Iterative Fibonacci

Product Sense & Metrics

Would you consider adding a payment feature to Facebook Messenger is a good business decision?

Messenger Payments

Forecasting & Time Series

Time Series Discrepancies

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>

Duplicate Rows

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?

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 function <code>fib</code> which takes an integer <code>n</code> and returns the nth fibonacci number. For this question, <code>fib</code> MUST be recursively defined.

Note: <code>for</code> and <code>while</code> keywords are disabled for this question, as well as <code>functools</code>. Any workarounds around this restriction is prohibited.

Example:

Input:

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

Output:

<pre tabindex="0" class="chroma"><code>def fib(n) -&gt; 3
# the sequence is [1, 1, 2, 3, 5, 8...]
</code></pre>

Imagine you work at a major credit card company and are given a dataset of 600,000 credit card transactions to build a fraud detection model.

How would you approach this task? Write your answer in the comments.

Build a logistic regression model from scratch, with the following conditions:

<ul>
<li>Return the parameters of the regression</li>
<li>Do not include an intercept term</li>
<li>Use basic gradient descent (with newton’s method) as your optimization method and the log-likelihood as your loss function.</li>
<li>Don’t include a penalty term.</li>
<li>You may use numpy and pandas but NOT scikit-learn</li>
</ul>

Example:

Input:

<pre tabindex="0" class="chroma"><code>step_size = 0.02
max_steps = 100
starting_point = np.asarray(data.drop(&#39;Target&#39;).mean())
print(data)
...
 Var1 Var2 Var3 Target
0 0.439326 -0.662463 0.027418 1
1 -1.363880 -1.303938 -1.595875 1
2 -1.710828 -2.473115 -0.968141 1
3 -1.620589 1.321073 1.608265 0
4 -0.315593 -1.655797 0.126860 0
.. ... ... ... ...
95 -0.663844 0.225382 0.650974 0
96 1.479807 0.322281 0.501116 0
97 0.510666 -0.745397 -0.239914 0
98 -0.769290 1.348070 -0.059427 0
99 2.018888 -0.945268 -0.851626 0

[100 rows x 4 columns]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>def logistic_regression(data,starting_point,step_size,steps) -&gt; [0.35155765,-0.30863254,-0.13125343]
</code></pre>

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

Facebook is considering implementing a payment feature into Facebook Messenger. The feature would allow friends to pay one another in a similar way to Venmo by sending a payment message.

How would you determine whether or not this is a good business decision?

What are the potential risks or drawbacks of implementing a payment feature on a social media platform?

What are the potential risks or drawbacks of implementing a payment feature on a social media platform?

You are given a list of <code>[x,y]</code> coordinates in a matrix called <code>X</code>.

Write a function using gradient descent to return a tuple describing the line of best fit for the given coordinates. The first number in the tuple should be the line’s slope. The second number in the tuple should be its y-intercept.

You may not import any libraries.

Example:

Input:

<pre tabindex="0" class="chroma"><code>coordinates = [(0, 1), (1, 3), (2, 2), (3, 4), (4, 6), (5, 5), (6, 7), (7, 9), (8, 8), (9, 10), (10, 12), (11, 11), (12, 13), (13, 15), (14, 14), (15, 16), (16, 18), (17, 17), (18, 19)]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>(1, 1) 
</code></pre>

Let’s say that you’re working at a global trading company and you’re analyzing the price of a particular asset over time. This dataset is super noisy, volatile, and you’re not guaranteed completely accurate data.

How would you analyze this data to ensure there aren’t any discrepancies?

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

Centrifuge Inc Interview Questions

Centrifuge Inc Interview Guides

Centrifuge Inc Interview Questions

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Discussion & Interview Experiences