Learn the fundamentals and strategies for interviewing for a data science job.

Product analytics interviews evaluate your skills and creativity as an aspiring data analyst. Interview questions evaluate if you can use your technical knowledge to guide further development of a product. Learning how to answer these questions is crucial to ace most job interviews for data scientists and analysts.

In this course, you’ll first gain an overview of what product analytics interviews look like and what kinds of questions usually come up. Next, you’ll learn to use a framework for answering product analytics questions, showcasing your analytical skills. Finally, you’ll learn how to apply said framework to different kinds of product analytics interview questions by looking at several examples.

With this course, you’ll increase your chances of landing a job in data science by learning how to effectively answer product analytics interview questions. You’ll be able to provide well-structured and well-communicated answers, and show you can creatively tackle any business problem you may face.

Ace the Product Analytics Job Interview

## Problem

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 by 5%, but email notification open rates are down 2%.

What would you investigate to diagnose what’s happening?

Try answering this on your own before continuing. Use the hints below if you are stuck.



# Problem

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 by 5%, but email notification open rates are down 2%.

What would you investigate to diagnose what’s happening?

Try answering this on your own before continuing. Use the hints below if you are stuck.



Try to solve this question to test your understanding of the material.


Sample Question: WAU vs. Open Rates

Try to solve this question to test your understanding of the material.

Introduction

Investigating Metrics

Fractional Metrics

Measuring Success

Feature Change

Metric Trade-Offs

Growth

Conclusion

Sample Question: WAU vs. Open Rates

Problem