Electronic Arts (EA) Data Analyst Interview Questions + Guide in 2024

Electronic Arts (EA) is a global leader in digital interactive entertainment, delivering games, content, and services for internet-connected consoles, mobile devices, and personal computers. As a Data Analyst, you will play a crucial role in shaping the future of game development and player experiences by leveraging data to enhance their products and services.

The Data Analyst positions within EA, such as those in the Frostbite team or at Respawn, involve diverse responsibilities like data modeling, statistical analysis, dashboard creation, and data governance. Ideal candidates will have strong technical skills in tools like SQL, Python, and Power BI, a robust foundation in mathematics and statistics, and the ability to translate complex data into actionable insights.

If you’re keen on a role that challenges you to analyze data-driven decision-making within the gaming industry, this guide will help you navigate the process and commonly asked Electronic Arts (EA) data analyst interview questions with confidence. Let’s get started!

The interview process usually depends on the role and seniority; however, you can expect the following on an Electronic Arts (EA) data analyst interview:

Recruiter/Hiring Manager Call Screening

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

Sometimes, the EA 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 invite you to the technical screening round. Technical screening for the EA Data Analyst role is usually conducted through virtual means, including video conference and screen sharing. Questions in this one-hour interview stage may revolve around EA’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. In addition, your proficiency in hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Case studies and similar real-scenario problems may also be assigned depending on the position’s seniority.

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 will be conducted during your day at the EA office, varying with the role. 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 EA.

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

1. Write a function to simulate coin tosses based on the number of tosses and probability of heads.

Write a function that takes an input as the number of tosses and a probability of heads and returns a list of randomly generated results equal in length to the number of tosses. Each result represents the outcome of a coin toss, where ‘H’ represents heads and ’T’ represents tails.

2. What is the formula for calculating the average lifetime value for a SAAS company?

You work for a SAAS company with a product costing $100/month, a 10% monthly churn rate, and an average customer lifespan of 3.5 months. Calculate the formula for the average lifetime value.

3. What metrics/graphs/models would you use to analyze churn behavior for different Netflix pricing plans?

Netflix has two pricing plans: $15/month or $100/year. An executive wants an analysis of churn behavior for these plans. What metrics, graphs, and models would you build to provide an overarching view of subscription performance?

4. How would you analyze cross-platform user interaction data to optimize user experience?

You need to analyze user interaction data on both web and mobile to understand behavior, preferences, and engagement patterns. Write a query to determine the percentage of users who visited only mobile, web, and both.

5. How would you select the best 10,000 customers for a pre-launch of a new show on Amazon Prime Video?

Amazon Prime Video wants to test a new show on 10,000 customers. How would you select these customers, and what would the pre-launch process look like to measure performance?

6. What would you expect to happen to the conversion rate after applying a new UI to all users?

A new UI tested on a random subset of users increased the target metric by 5%. If the new UI were applied to all users, what would you expect to happen to the metric, assuming no novelty effect?

7. 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 whether a borrower will repay a personal loan. How would you evaluate if a decision tree is the right model for this problem? How would you evaluate the model’s performance before and after deployment?

8. What is the concept of LDA in machine learning and its use cases?

Explain the concept of Linear Discriminant Analysis (LDA) in machine learning. What are some practical use cases for using LDA?

9. How would you collect and aggregate unstructured video data for an ETL pipeline?

You are designing an ETL pipeline for a model that inputs videos. How would you collect and aggregate data for multimedia information, specifically unstructured data from videos?

10. How would you create a system to detect firearm listings on a marketplace?

You are designing a marketplace for your website where selling firearms is prohibited. How would you create a system to detect if a listing is selling a gun automatically?

11. How would you design a YouTube video recommendation algorithm?

You are tasked with building the YouTube video recommendation algorithm. How would you design the recommendation system? What important factors should be considered when building the recommendation algorithm?

To help you succeed in your Electronic Arts (EA) data analyst interviews, consider these tips based on interview experiences:

1. Familiarize with EA’s Products: EA questions may include situational scenarios involving their games and services. Study EA’s games and think about how you would improve or analyze them using data.

2. Showcase Collaboration Skills: EA values teamwork highly within their game development process. Be prepared to discuss past experiences where you’ve worked collaboratively on data projects.

3. Stay Persistent: The interview process can be lengthy—ensure consistent follow-up and maintain communication to leave a lasting positive impression.

What is the average salary for a Data Analyst at Electronic Arts (Ea)?

What kind of technical skills should I have for a Data Analyst position at EA?

You should have strong technical skills in SQL, Python, and business intelligence tools like Power BI or Tableau. Experience with cloud computing platforms such as Azure, AWS, or GCP is also beneficial. Proficiency in statistical analysis and data visualization is essential, as well as a solid foundation in mathematical and statistical knowledge.

What responsibilities will I have as a Data Analyst at EA?

As a Data Analyst at EA, you’ll work on projects that empower game developers by providing them with data-driven insights. Your responsibilities will include analyzing operational data, developing and maintaining scripts and queries, constructing dashboards and reports, conducting statistical analyses, and presenting complex data findings clearly and clearly to non-technical partners.

What is the work environment and culture like at EA?

Electronic Arts fosters a diverse and inclusive culture. The company values creativity, innovation, and collaboration. EA offers a holistic benefits program focusing on physical, emotional, financial, career, and community wellness to support employees throughout their lives. You’ll be able to work with passionate and talented teams dedicated to producing amazing games and experiences for players worldwide.

Embarking on a journey with Electronic Arts (EA) as a Data Analyst offers a compelling opportunity to shape the future of gaming through innovative data-driven solutions. The company provides a vibrant platform where your technical and analytical skills can significantly impact world-class gaming experiences.

If you want more insights about the company, check out our main Electronic Arts Interview Guide, where we’ve covered other interview questions that could be asked.

You can also check out all our company interview guides for better preparation.

Good luck with your interview!