Electronic Arts

About the Team

The Ventures Innovation team at Electronic Arts is dedicated to exploring new opportunities beyond the bounds of traditional gaming; specifically new opportunities across the rapidly evolving industry as well as disruptive forms of sports entertainment. 

As part of the Experiences organization, we are a forward-thinking team of innovators, strategists, creatives, engineers, and statisticians. Together, we incubate disruptive products, features, and capabilities that sit outside the core gaming experiences of EA, breaking new ground in interactive experiences and sports entertainment.

The Role

And we want you to join us. We are hiring a Lead Data Scientist for our EA Ventures organization, reporting to our Director of Innovation.  Your mission is to bring ideas to life by harnessing the latest technologies (and data!) to define the future of interactive entertainment. 

Your Responsibilities:

• Design and build NLP/ML/AI models integrated into new player-facing products, leveraging cutting edge technology to shape the future of interactive entertainment

• Build effective relationships with Engineering Leads, Product Designers and other partners to create requirements and execute new data-powered experiences

• Identify, source, examine, clean, visualize and prep datasets for statistical analysis

• Deploy models for production into AWS SageMaker and work with our technical partners across EA to identify and manage proper data feeds

• Communicate modeling results in business-friendly language to partners and department leadership, driving effective business decisions.

• Measure and monitor model accuracy over time, manage model drift; retrain model when accuracy drops below agreed-upon threshold

• Assist in designing A/B tests, including determining hypotheses, lift and sample size calculations and runtime recommendations

Your Qualifications:

• Master’s in computer science, mathematics, or related field, with experience in research and development

• Experience with machine learning and familiarity with multiple ML techniques. Expert in at least one Statistical Programming Language such as R or Python

• Experience with AWS SageMaker

• Demonstrated success turning new ideas into effective implementations

Job-specific technical skills

• Expert in Data ingestion and munging, like extracting elements of a json object, feature extraction, stratified sampling and dimensionality reduction techniques (i.e. Principal Component Analysis)

• Expert in Exploratory Data Analysis including visualizations, summary statistics, identifying and imputing missing data and checking for data quality problems

• Expert in statistical concepts such as descriptive statistics, percentiles and outliers, central limit theorem, distance measures, probability theory, bayes theorem, continuous distributions, hypothesis testing and regression modeling

• Experience with unsupervised and supervised Machine Learning models (i.e. Decision trees, Naive Bayes, Clustering, Ranking, Classification) as well as Machine Learning concepts like boosting, dealing with imbalanced classes, train, test vs. validation set and overfitting

• Bonus: Experience with NLP concepts such as Named Entity Recognition, constructing Document-Term-Matrices, Topic Modeling, Text Classification and LLMs

• Bonus: Experience with model lifecycle management concepts such as model bias and drift, constructing data labeling jobs for collection of 'golden dataset', and model deployment, monitoring and decommissioning in AWS SageMaker

Job-specific soft skills

• Player Centric – You put the consumer at the center when designing new offerings and processes.  You understand how decisions and work impact the player.

• Learner – You have a passion for learning new technologies, products, and consumer behaviors.  You are passionate about using data to inform insights into new opportunities

• Team Player – You can work with a cross-functional team, understanding how your skills complement those around you to build the best experiences for customers

• Documentation Expert – You know just the right level of documentation to share your learnings and set up the broader teams for success when new ideas take flight

• Teacher – You are patient and can field questions from team members around better coding practices or statistics related problems

• Experiment Designer – You can create up an A/B test in your sleep, but you don't let a less than ideal A/B test set up stop you from finding some answers

• NLP fanatic – You can turn language into math? Yeah – that's the stuff you love!