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Sr. Channel Strategist; Web Experimentation & Personalization

Job in Austin, Travis County, Texas, 78716, USA
Listing for: Electronic Arts
Full Time position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Position: Sr. Channel Strategist (Web Experimentation & Personalization)

Locations
:

  • Austin, Texas, United States of America
  • Vancouver, British Columbia, Canada
  • Vancouver - Great Northern Way, British Columbia, Canada
  • Galway, Ireland

Role

Worker Type:
Regular Employee

Studio/Department:
Fan Growth

Work Model:
Hybrid

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.

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.
Skills and Experience
  • 3-7 years of relevant experience in a CXor marketing environment.
  • 2+ years of experience in digital experimentation, optimization, or personalization, ideally on large, consumer-facing websites.
  • Hands-on experience with Optimizely (required) – including test setup, targeting, results analysis, and QA.
  • Strong understanding of A/B testing methodologies, experiment design, sample sizing, and statistical models (Bayesian, Sequential, Frequentist).
  • Experience using experimentation for segmentation, personalization and experience optimization, not just conversion testing.
  • Ability to synthesize qualitative and quantitative data to identify insights and drive recommendations.
  • Ability to turn complex data into clear, actionable insights for technical and non-technical audiences.
  • Awareness of data privacy and compliance frameworks (GDPR, consent management, accessibility standards).
  • Comfortable working with Product, Engineering, and…
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