- 地点: Vancouver
- 州: British Columbia
- 国家/地区: Canada
- 地点: Toronto
- 州: Ontario
- 国家/地区: Canada
We're hiring an Advanced Analyst for our Data and Insights team, where our job is to use statistical skills, research methodologies, and data analysis to represent the voice of the player. Reporting to a Director of Analytics, you will partner with developers and leaders across a portfolio of ARPG titles to provide impactful analysis with relevant takeaways. In addition to working with our studio partners, you will also have opportunities to collaborate and share with other data experts among the larger data analytics community at EA. As a team of analysts and researchers, we understand how important teaching, learning, and growth are.
Responsibilities:
Champion analytics projects from the conceptual stages through communication of results and recommendations
Use player data to perform behavioral analysis, clustering analysis, predictive modeling, hypothesis testing, and more
Utilize third-party data to make inferences about the competitive landscape and inform decision-making
Partner with designers, product managers, producers, and engineers to establish the data needed from a game to understand how players engage with its features and systems
Partner with executives to establish and execute research roadmaps that impact decision making
Engage with peers to develop and share best practices, and establish subject matter expertise in core game analytics
Develop dashboards and visualizations to monitor important game features and business health, applying automation and insights when relevant
Support game launch and live operation of titles by testing and reporting on acquisition, engagement, retention, and monetization funnels
Requirements:
5+ years of experience applying quantitative or statistical methods to produce insights from data
Experience presenting technical findings to audiences with varying backgrounds and demonstrable ability to engage with senior leaders
SQL proficiency and the ability to extract data from large data sources with differing structures
Proficiency with a statistical analysis tool (such as R or Python) to perform analysis
Proficiency with a data visualization tool (such as Looker) to build clear, user-friendly data visualizations, tables, and dashboards
Familiarity with version control and reproducible research best practices
Ability to flexibly adjust priorities given the demands of creation in an innovative new space