Senior Channel Strategist (Web Experimentation & Personalization) · Electronic Arts

Fri, 24 Apr 2026 13:14:37 GMT
Engineering

Electronic Arts · Austin · $92,900 - $129,200 CAD · hybrid

We're hiring a Web Experimentation Strategist to drive the design, execution, and analysis of experiments that shape the EA Help web experience. The Senior Channel Strategist (Web Experimentation & Personalization) will use Optimizely to test and personalize digital experiences, help fans get the right help faster, and deepen engagement across EA's support ecosystem.

In this role, you'll turn hypotheses into measurable experiments, advise on test design to ensure validity and statistical significance, and help partners translate learnings into next steps. You'll partner closely with Product, Engineering, and Analytics teams to build a culture of test-and-learn, establish governance standards, and ensure we stay within platform usage limits.

This role turns experimentation into personalization, making every web experience more responsive to who the fan is and what they need.

Responsibilities:

Build the experimentation program for EA Help,designing, setting up, and managing A/B and multivariate tests in Optimizely.

Define and maintain experimentation governance, including test intake, prioritization, and documentation processes to ensure consistent, scalable execution.

Advise on experiment design to ensure tests are statistically valid and align with business goals.

Set up and launch experiments directly in Optimizely, or partner with Engineering for server-side or complex technical implementations.

Analyze and interpret experiment results, producing actionable insights, business narratives, and recommendations for next steps.

Develop personalization strategies using segmentation, targeting, and behavioral data to tailor content to specific fan groups or individuals.

Integrate qualitative research and fan feedback to validate hypotheses and enrich quantitative findings.

Pilot new workflows, tools, or automations that improve experimentation velocity, reliability, and transparency.

Foster a “learn fast” mindset, normalizing failed tests as valuable learning and celebrating insights as much as wins.

Collaborate cross-functionally with Product, Analytics, and Content teams to identify and prioritize opportunities for testing and personalization.

Track and report on the performance, adoption, and impact of experimentation across initiatives.

Monitor platform usage to ensure we stay within monthly active user (MAU) limits and avoid overage charges.

Stay informed on AI-driven user experiences and explore opportunities to leverage AI for experimentation, personalization, and insights generation.

Champion experimentation culture, coaching partners and team members to use data to inform design and content decisions.