Prepare for and practice interview questions from Eastman across topics like Algorithms, Statistics, Machine Learning and more.

Eastman Interview Questions

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Machine Learning

Booking Regression

Lasso vs Ridge

Find the linear regression parameters of a given matrix

Linear Regression Parameters

Statistics

What are the assumptions of linear regression?

Assumptions of Linear Regression

Correlation in Regression

What are the regression coefficients when regressing Y on X versus X on Y, given Y = X plus normal white noise?

Regress Y on X

Analytics

Describing a data project and its challenges

Hurdles In Data Projects

Strategically resolving misaligned expectations with stakeholders for a successful project outcome

Stakeholder Communication

Data Pipelines

Describing a real-world data cleaning and organization project

Data Cleaning Experiences

Business Case

Vision Setting and Execution Strategy

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

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

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

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

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

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 do you detect and handle correlation between variables in linear regression? What will happen if you ignore the correlation in the regression model?

Describe a time when you had to define a long-term vision for a project or team and move it from concept to reality.

Interviews for leadership or senior technical roles look for more than just “finishing a project.” Your answer should specifically address:

<ol>
<li>The “Why”: What data or organizational gap necessitated this vision?</li>
<li>The Framework: How did you translate a high-level goal into a roadmap?</li>
<li>The Friction: How did you handle stakeholders or team members who were skeptical of the new direction?</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 we want to build a model to predict booking prices on Airbnb.

Between linear regression and random forest regression, which model would perform better and why?

What are the two key concepts of random forest regression?

What are the two key concepts of random forest regression?

Suppose we have two variables, X and Y, where Y = X + some normal white noise.

<ol>
<li>What will our coefficient be if we run a regression of Y on X?</li>

<li>What happens if we run a regression of X on Y?</li>
</ol>

Given a matrix of X and y values, write a function to generate a transposed matrix and estimate the parameters for linear regression.

Example:

Input:

<pre tabindex="0" class="chroma"><code>A = [[1, 5], [4,8], [5,9]]

</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>#Output
linear_regression(A) -&gt; [[[1, 4, 5], [5, 8, 9]] , [4, 1]]
</code></pre>

Note: Return the solutions a list of `[[A_T] , [coefficients]]

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