Newsela is an innovative education technology platform that aims to transform the way students engage with learning content. By providing leveled reading material across various subjects, Newsela helps educators tailor lessons to meet the diverse needs of every student.

The Data Analyst position at Newsela requires proficiency in data extraction, analysis, and interpretation to support product development and business strategy. As a Data Analyst, you'll be expected to apply statistical techniques, work with large datasets, and generate actionable insights that drive decision-making across the organization.

If you aspire to be part of a company dedicated to making education more accessible and effective, this guide will help you prepare for the Data Analyst interview at Newsela. Here, we will cover essential insights into the interview process and share some key questions and tips to help you ace your interview.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Newsela as a data analyst. Whether you were contacted by a Newsela recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Newsela Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Newsela data analyst hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Newsela data analyst role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Newsela’s data systems, ETL pipelines, and SQL queries.

In the case of data analyst roles, take-home assignments regarding product metrics, analytics, and data visualization are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Newsela office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the data analyst role at Newsela.

Quick Tips For Newsela Data Analyst Interviews

• Data Visualization: Ensure you are proficient in data visualization tools and techniques. Newsela heavily values the ability to present data in an easily interpretable manner.
• SQL Proficiency: Master SQL queries, including joins, subqueries, and aggregate functions, as they tend to be a significant part of the technical screening process.
• Cultural Fit: Newsela values a collaborative and innovative work culture. Practice response to behavioral questions that reflect these values.

Typically, interviews at Newsela vary by role and team, but commonly Data Analyst interviews follow a fairly standardized process across these question topics.

• What metrics would you use to determine the value of each marketing channel? Given all the different marketing channels and their respective costs at Mode, a company selling B2B analytics dashboards, what metrics would you use to evaluate the value of each marketing channel?

• How would you measure the success of the banner ad strategy? An online media company wants to experiment with adding web banners into the middle of its reading content to monetize web traffic. How would you measure the success of this banner ad strategy?

• How would you analyze the performance of a new feature without an A/B test? LinkedIn has launched a feature allowing candidates to message hiring managers directly during the interview process but cannot A/B test it due to engineering constraints. How would you analyze the feature's performance?

• How would you measure the health of the Mentions app and attribute engagement increases? Facebook is rolling out "Mentions," an app for celebrities to connect with fans. How would you measure the app's health, and how would you attribute increases in fan engagement to the app versus the celebrity's own efforts?

• What would you investigate to diagnose changes in user engagement and email open rates? A product manager reports that weekly active users are up 5%, but email notification open rates are down 2%. What would you investigate to diagnose this situation?

• Write a function pick_host to determine the optimal friend to host a party based on location. Given a group of (N) friends represented by a list of dictionaries where each value is a friend's name and their location on a three-dimensional scale ((x, y, z)), write a function pick_host to return the friend that should host the party. The goal is to minimize the total travel distance for the group.

• How would you evaluate whether using a decision tree algorithm is the correct model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will pay back a personal loan. How would you evaluate if a decision tree is the right choice? If you proceed, how would you evaluate the model's performance before and after deployment?

• How would you determine if a new delivery time estimate model is better than the old one? You want to build a new delivery time estimate model for food delivery. How would you compare its predictions to the old model to determine which is better?

• How would you determine which search engine performed better and which metrics to track? You are building a better search engine for Google and want to compare it to the existing one. How would you determine which search engine performed better, and which metrics would you track?

• What are the benefits of dynamic pricing, and how can you estimate supply and demand? Explain the benefits of dynamic pricing. How would you estimate supply and demand in this context?

• How would you design a machine learning model to classify major health issues based on health features? You work for a health insurance company and need to design a machine learning model to classify if an individual will undergo major health issues based on a set of health features. How would you approach this task?

• What is an unbiased estimator and can you provide an example for a layman to understand? Explain what an unbiased estimator is in simple terms and provide an easy-to-understand example.

• What are the benefits of dynamic pricing, and how can you estimate supply and demand in this context? Describe the advantages of dynamic pricing and explain how to estimate supply and demand when using this pricing strategy.

• How would you design a machine learning model to predict major health issues? As a machine learning engineer for a health insurance company, design a model that classifies individuals based on health features to predict if they will undergo major health issues.

If you want more insights about the company, check out our main Newsela Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Newsela’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Newsela Data Analyst interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!