Data Scientist

Electronic Arts

Hybrid

Quick summary

Work type: Hybrid
Location: Austin, TX
Posted: 7 days ago
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $158k

$88k most similar roles pay here $215k

This listing doesn't post a salary. Most similar roles pay $126,800–$189,745.

Based on 240 similar postings.

Employer

About Electronic Arts

Electronic Arts is a global leader in digital interactive entertainment, developing and publishing games for consoles, mobile, and PC under franchises including FIFA, Madden NFL, The Sims, Apex Legends, and Battlefield.

Electronic Arts currently has 90 open roles on FindRole.

Listed pay typically runs $122,300–$174,550 across 44 roles with salary data.

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At a glance

TL;DR · Data Scientist

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The Senior Data Scientist role at Electronic Arts’s Central Technology Security team in Austin involves leading data science initiatives to protect game integrity and player trust. This includes developing statistical and machine learning models to detect cheating, botting, payment fraud, and other suspicious behaviors using large datasets from gameplay telemetry, player behavior, and transaction records. The ideal candidate will have 5+ years of experience in data science or related fields, proficiency with Python or R, and expertise in model evaluation techniques. Familiarity with cloud platforms like AWS, GCP, and data processing tools such as Spark and Databricks is preferred. This role requires strong collaboration skills to work effectively across engineering, security, and game teams while communicating complex analytical insights clearly to both technical and non-technical stakeholders.

Skills

Python R SQL AWS GCP Spark Databricks Snowflake Hive Kafka Airflow Kubernetes CI/CD

What you'll do

Lead data science work across the model lifecycle, from analysis to deployment.
Design and develop models to detect cheating, botting, account abuse, and payment fraud.
Build features and risk signals using gameplay telemetry, player behavior, and transaction data.
Continuously evaluate model performance and adapt to evolving abuse patterns.
Communicate analytical findings clearly to technical and non-technical stakeholders.

What we're looking for

5+ years of experience in data science, machine learning, or related analytical fields.
Strong proficiency with Python and advanced SQL for data analysis.
Experience building statistical models using large-scale behavioral and transactional data.
Expertise in model evaluation techniques including precision-recall tradeoffs and noisy labels.
Ability to collaborate cross-functionally and communicate complex findings effectively.

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