EA SPORTS is one of the leading sports entertainment brands in the world, with top-selling videogame franchises, award-winning interactive technology, fan programs, and cross-platform digital experiences. EA SPORTS creates connected experiences that ignite the emotion of sport through industry-leading sports video games, including Madden NFL football, EA SPORTS College Football , EA Sports FC, NHL hockey, NBA LIVE basketball, and EA SPORTS UFC.
EA SPORTS Madden NFL is the best-selling sports property in U.S. video game history. Madden NFL is an immersive, simulation-based, authentic NFL interactive experience that empowers fans to play out their NFL fantasies. Madden NFL has entertained fans for over three decades with more than 130 million lifetime units sold. The highly anticipated EA SPORTS College Football launched with record-breaking unique players, returning to a much-loved sport, reimagined for a new generation of platforms, breaking new ground with athletes through the world's largest single-sport NIL program, and delivering an experience that has ignited college football fans both long-time and new, around the US and across the world.
College Football and Madden NFL are developed at EA's Tiburon Studio in Orlando, FL, and Madrid, Spain by a team that prides itself on innovation and creative collaboration. We're looking for talent with an experience with sports games to create experiences that connect with football fans around the world to grow the love of the sport.
Reporting to the Director of Product Management, as a Senior Game Product Manager, you will work in collaboration with the design team to spec game features and systems to drive key business metrics. You will build validation strategies for features through a combination of data analysis, user research, and A/B testing. You will be a key contributor and thought leader in designing to meet player motivations within a fast paced, action oriented multiplayer sports game.
Responsibilities
- Authors specs for essential features that further the strategic vision of the product, and improve retention, acquisition, and monetization.
- Builds product forecasts that incorporate assumptions around feature impact on acquisition, retention, and monetization.
- Defines KPIs and corresponding telemetry requirements for new features.
- Develops expected outcome framework and corresponding success criteria for small and large features introduced into product. Builds corresponding models.
- Models, builds, and tunes complex game economy systems with multiple currencies, progression systems, sinks, faucets, and player trading.
- Partners with UX researchers to gather qualitative insights from playtests.
- Informs prioritization and design of multiple features through knowledge of competitors, deep understanding of the player, and scenario analysis.
- Builds partnerships with Central teams and crafts requirements for player facing features outside of game team's scope
What will they do
- Builds models to forecast business performance, support scenario planning, and inform product roadmap
- Leverages experience and research from qualitative and quantitative data sources to develop an advanced level of understanding of player motivations, personas and segmentations.
- Collaborates with stakeholders to derive and collate qualitative and quantitative inputs that serve as validation points for development, e.g., User Research, Consumer Insights, Analytics.
- Stays informed on performance of and innovations in major new game releases.
- Performs teardown analysis on products and releases relevant to the strategic vision of the product.
Qualifications:
- A passion for games with a player first mentality
- Bachelor's Degree in Economics, Finance, Statistics, Marketing, Business, or Social Science.
- 5+ years of Product Management or other relevant Game discipline experience required (Live Services preferred).
- The ability to critically evaluate design, UX, and economy that influence player behavior
- Strong analytical skills and experience with data driven product design and decision making
- Experience with using tools to efficiently collate, clean, and analyze data from mixed sources (e.g., Python, R, Tableau, STATA, SQL)
- Basic knowledge of statistical methods for evaluating hypotheses (e.g., A/B testing, linear regression, bootstrapping)
- Highly desirable, but not essential: A passionate football fan.
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