Electronic Arts

The Office of the CXO drives effectiveness across the EA Experiences organization with a focus on excellence in business operations, comprehensive fan intelligence, plus internal technology and business solutions. We are horizontal connectors empowering teams across the Experiences organization with the strategic prioritization, investments, resources, data, insights, and technology required to accelerate business outcomes in service of our goals.

And we want you to join us. We are hiring a Senior Data Scientist for our CXO Data & Analytics team, reporting to the Marketing Data Science Senior Manager. This is an individual contributor role with no managerial responsibilities.

Main Responsibilities:

• Develop predictive models and ML algorithms for campaign planning, optimization, and impact measurement. 

• Design, execute, and analyze controlled experiments and use causal inference to quantify the business impact of interventions and offers. 

• Cross-functional collaboration with Analytics, Brand, and Fan Care teams to gather requirements and develop data-driven solutions that align with business objectives.

• Enable data-driven decision-making using data storytelling and effective communication to present findings to stakeholders with a diverse background. 

• Write clean and production-ready Python or R code. Use SQL to develop ETL processes to gather and aggregate data across different databases. 

• Model deployment in a production environment (AWS SageMaker) with continuous monitoring, retraining, and redeployment of models.  

Required Qualifications:

• PhD or Master's degree in quantitative or engineering. 

• 5 years of relevant work experience in the industrial domain with demonstrated expertise in applying data science, statistical modeling, and machine learning in Marketing.

• Proficiency in writing clean and professional code in Python and R for data analysis, modeling, and visualization. Hands-on skill in SQL is required. 

• Demonstrate advanced machine learning skills, such as feature stores and feature selection, and have experience developing and deploying ML models in cloud-based production environments. 

• Excellent data storytelling and the ability to communicate highly technical concepts to a diverse audience verbally and in writing. 

• Critical thinking and the eagerness to suggest creative ways to overcome problems with a player-centric mindset while ensuring fairness and inclusivity of the solutions.

• Experience with cloud-based machine learning environments such as AWS SageMaker.