This job might no longer be available.

Sr Data Scientist

Senior Data Scientist

Electronic Arts

Austin, TX

Our Worldwide Customer Experience (WWCE) team exists to help the world play. We support players across the globe in 13+ languages and value employees that will bring new ideas and perspectives to help make WWCE a great place to be and be from. We celebrate diversity and inclusion and aim to create great experiences for our employees as often as our players. We are looking for people that will come to the office or Zoom meeting excited to work and ready for some fun.

And we want you to join us. We are hiring a Senior Data Scientist for our WWCE Insights team, reporting to the Director of Data Science for WWCE.

Responsibilities:

• Identify, source, examine, clean, visualize and prep datasets for statistical analysis
• Model datasets and perform model fit tests
• Build effective relationships with Product Managers and other partners to identify and execute new Data Science opportunities across the WWCE Department and EA at large
• Communicate modeling results in business-friendly language to partners and department leadership by building PowerPoint presentations
• Deploy models for production into AWS SageMaker and work with our IT department to identify the necessary data feeds so models can produce inference
• Work with our UX designers to decide how model results will be shown in an application
• Monitor model accuracy over time and keep an eye out for model drift; retrain model when accuracy drops below agreed-upon threshold
• Periodically report back to partners on model performance

Qualifications:

• 3 or more years experience in Data Science with some experience in NLP
• Master's in Statistics, Operations Research or related field (we will consider a Bachelor's degree with significant relevant experience)
• PMP certification a plus for leading large projects

Technical skills:

• Expert in at least one Statistical Programming Language such as R or Python Experience with relational and distributed databases
• Experience with any of the following is a big plus: PySpark, Scala, Zepplin Notebooks, Spark and MLlib as well as application development using AWS, Virtual Machines, or Docker
• Experience with AWS SageMaker

Job-specific 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 and Text Classification
• 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

People skills

• Customer Advocate – You care what kind of experience our players are having when their games or services don't work and you want to play your part in improving it
• Programmer – You're an expert at writing functions and identifying the right language for the right situation
• People Analyst – You understand that your work contributes to improving people's lives not predict when a machine is going to break down
• Learner – You are a regular on Stack Overflow, know how to take apart a Vignette and are always looking for a new project that allows you to put that cutting edge technique to good use you read about last month
• Documentation Expert – You know just the right level of documentation to help yourself and the person who takes over after you understand what you did, when and why
• Teacher – Y ou 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!