Sr Data Scientist

Electronic Arts (EA); Vancouver; On-site; CAD 141,000 - 204,000; Full time

Job summary

Electronic Arts is seeking a senior data scientist to lead end-to-end data science initiatives within EA Security in Vancouver, BC. You will design and deploy ML models to detect cheating, fraud, and platform risks, collaborating with engineering, product, and security teams.

You will mentor junior data scientists, build scalable features from telemetry data, and define evaluation and monitoring practices to ensure robust, explainable results in production.

Qualifications

• 7+ years of experience in Data Science, Machine Learning, Applied Statistics, Fraud Detection, Security Analytics, Trust & Safety, or a related analytical field.
• Strong proficiency in Python or R and advanced SQL.
• Experience leading end-to-end machine learning projects from ambiguous problem definition through production deployment.
• Expertise building statistical or machine learning models using large-scale behavioral, transactional, telemetry, account, or security datasets.
• Strong understanding of model evaluation, including precision/recall tradeoffs, threshold optimization, calibration, false positives, monitoring, and model performance measurement.
• Experience engineering features from complex, multi-source datasets and translating business or security problems into scalable analytical solutions.
• Proven ability to partner cross-functionally with engineering, product, security, fraud, or operations teams to deliver production-ready models, dashboards, and decision-support tools.
• Experience mentoring technical teammates and effectively communicating complex analytical insights to diverse audiences.

Responsibilities

• Lead end-to-end data science initiatives, from problem definition and exploratory analysis through model development, evaluation, deployment, and monitoring.
• Design and develop statistical and machine learning models to detect cheating, fraud, account abuse, botting, suspicious gameplay, and other emerging platform risks.
• Build scalable features, risk signals, and detection frameworks using gameplay telemetry, player behavior, account, transaction, and operational data.
• Investigate complex abuse patterns, translate insights into models, rules, dashboards, and recommendations, and continuously improve detection quality by optimizing model performance and reducing false positives.
• Establish best practices for model evaluation, monitoring, drift detection, and impact measurement while partnering with engineering teams to productionize data science solutions.
• Collaborate with product, security, anti-cheat, fraud, game, and operations teams to develop data-driven prevention and enforcement strategies.
• Mentor junior data scientists, promote reusable data science practices, and communicate analytical findings, model tradeoffs, and business impact to technical and non-technical stakeholders.

Skills

Python or R

SQL

Machine Learning

Data Science

Model evaluation

Cross-functional collaboration

Mentoring

Tools

AWS/GCP

Spark

Databricks

Kubernetes

Job description

Description & Requirements

Electronic Arts creates next-level entertainment experiences that inspire players and fans around the world. Here, everyone is part of the story. Part of a community that connects across the globe. A place where creativity thrives, new perspectives are invited, and ideas matter. A team where everyone makes play happen.

Central Technology is the force multiplier, accelerating creative opportunity and progress at EA. We’re a world-class community of technologists, innovators, strategists, and orchestrators transforming interactive entertainment. Together, we power the platforms, AI-driven tools, live services, and infrastructure that ensure global scale, secure player experiences, and unlock bold new possibilities.

EA Security protects our players, employees, products, and platforms. We set security standards, support game and enterprise teams, assess risk across partners and systems, and ensure compliance with global requirements. Our work strengthens system integrity, supports fair play, and enables teams to build and operate securely at scale.

Responsibilities

• Lead end-to-end data science initiatives, from problem definition and exploratory analysis through model development, evaluation, deployment, and monitoring.
• Design and develop statistical and machine learning models to detect cheating, fraud, account abuse, botting, suspicious gameplay, and other emerging platform risks.
• Build scalable features, risk signals, and detection frameworks using gameplay telemetry, player behavior, account, transaction, and operational data.
• Investigate complex abuse patterns, translate insights into models, rules, dashboards, and recommendations, and continuously improve detection quality by optimizing model performance and reducing false positives.
• Establish best practices for model evaluation, monitoring, drift detection, and impact measurement while partnering with engineering teams to productionize data science solutions.
• Collaborate with product, security, anti-cheat, fraud, game, and operations teams to develop data-driven prevention and enforcement strategies.
• Mentor junior data scientists, promote reusable data science practices, and communicate analytical findings, model tradeoffs, and business impact to technical and non-technical stakeholders.

Required Qualifications

• 7+ years of experience in Data Science, Machine Learning, Applied Statistics, Fraud Detection, Security Analytics, Trust & Safety, or a related analytical field.
• Strong proficiency in Python or R and advanced SQL.
• Experience leading end-to-end machine learning projects from ambiguous problem definition through production deployment.
• Expertise building statistical or machine learning models using large-scale behavioral, transactional, telemetry, account, or security datasets.
• Strong understanding of model evaluation, including precision/recall tradeoffs, threshold optimization, calibration, false positives, monitoring, and model performance measurement.
• Experience engineering features from complex, multi-source datasets and translating business or security problems into scalable analytical solutions.
• Proven ability to partner cross-functionally with engineering, product, security, fraud, or operations teams to deliver production-ready models, dashboards, and decision-support tools.
• Experience mentoring technical teammates and effectively communicating complex analytical insights to diverse audiences.

Preferred Qualifications

• Experience in gaming, anti-cheat, trust & safety, fraud prevention, cybersecurity, account abuse, bot detection, or other adversarial environments.
• Experience developing detection frameworks, risk scoring models, anomaly detection, graph analytics, clustering, sequence modeling, or human-in-the-loop review systems.
• Familiarity with gameplay telemetry, player behavior analytics, account lifecycle data, commerce systems, or live-service game operations.
• Experience operationalizing ML solutions with cloud and data platforms such as AWS, GCP, Spark, Databricks, Snowflake, Kafka, Airflow, or Kubernetes.
• Experience balancing detection effectiveness with player experience, operational efficiency, and business impact in rapidly evolving threat environments.

Pay Transparency - North America

Compensation And Benefits

The ranges listed below are what EA in good faith expects to pay applicants for this role in these locations at the time of this posting. If you reside in a different location, a recruiter will advise on the applicable range and benefits. Pay offered will be determined based on a number of relevant business and candidate factors (e.g. education, qualifications, certifications, experience, skills, geographic location, or business needs).

PAY RANGES

• British Columbia (depending on location e.g. Vancouver vs. Victoria) *$141,400 - $204,400 CAD
• California (depending on location e.g. Los Angeles vs. San Francisco) *$165,000 - $256,000 USD

Pay is just one part of the overall compensation at EA.

In the US, we offer a package of benefits including paid time off (3 weeks per year to start), 80 hours per year of sick time, 16 paid company holidays per year, 10 weeks paid time off to bond with baby, medical/dental/vision insurance, life insurance, disability insurance, and 401(k) to regular full-time employees. Certain roles may also be eligible for bonus and other incentive programs.

For Canada, we offer a package of benefits including vacation (3 weeks per year to start), 10 days per year of sick time, paid top-up to EI/QPIP benefits up to 100% of base salary when you welcome a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave), extended health/dental/vision coverage, life insurance, disability insurance, retirement plan to regular full-time employees. Certain roles may also be eligible for bonus and other incentive programs.

About Electronic Arts

We’re proud to have an extensive portfolio of games and experiences, locations around the world, and opportunities across EA. We value adaptability, resilience, creativity, and curiosity. From leadership that brings out your potential, to creating space for learning and experimenting, we empower you to do great work and pursue opportunities for growth.

We adopt a holistic approach to our benefits programs, emphasizing physical, emotional, financial, career, and community wellness to support a balanced life. Our packages are tailored to meet local needs and may include healthcare coverage, mental well-being support, retirement savings, paid time off, family leaves, complimentary games, and more. We nurture environments where our teams can always bring their best to what they do.

Electronic Arts is an equal opportunity employer. All employment decisions are made without regard to race, color, national origin, ancestry, sex, gender, gender identity or expression, sexual orientation, age, genetic information, religion, disability, medical condition, pregnancy, marital status, family status, veteran status, or any other characteristic protected by law. We will also consider employment qualified applicants with criminal records in accordance with applicable law. EA also makes workplace accommodations for qualified individuals with disabilities as required by applicable law.