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Senior Data Scientist
  • Python
  • Spark
  • SQL
  • Machine Learning
  • Big Data
  • Excel
  • Scala
  • Deep Learning
  • Keras
Electronic Arts
Redwood City, CA 94065
137 days ago
We are EA

And we make games – how cool is that? In fact, we entertain millions of people across the globe with the most amazing and immersive interactive software in the industry. But making games is challenging work. That’s why we employ the most creative, passionate people in the industry.

About the Role

This Senior Data Scientist is an important position in our Data Science team within the EA Studios organization at Electronic Arts, tasked with driving excellence and pushing innovation across EA. You will use your expertise in applied machine learning and artificial intelligence to guide essential decisions in a cross-functional environment. Our lead data scientist will directly help our games by developing complex and scalable data products.

We are looking for a team player who is able to work collaboratively within different game studios. You are eager to use data for insights and have a demonstrated passion for applying data science to make business critical decisions and recommendations. You desire to stay on the cutting edge, going out of their way to find and learn the "latest and greatest".

Come use your data superpowers for good and join us!
Develop meaningful relationships with partners throughout the studio organization to identify new opportunities for the team, both in addressing partners’ different pain points and proposing machine-learning-aided innovations to player experience. Research and build impactful data products that improve player experiences, driving them from conception, to experimentation, to productionization in-game. Contribute to the architecture and development of model deployment platforms, in particular providing guidance on automated model re-training, online training, scalability, failure recovery, updates with minimal downtime, model/pipeline versioning, performance monitoring. Stay up-to-date on latest developments in machine learning best practices, technologies, and research so as to expand the range of opportunities the team can handle.

Technical Qualifications
A PhD/MS in Computer Science, Artificial Intelligence, Statistics, Physics or related quantitative field 4+ years of experience applying data science/machine learning/deep learning methodologies to real-world problems Expertise in analyzing extremely large, complex, multi-dimensional data sets with a variety of tools, including Python, SQL, and Spark. Experience with big data technologies, distributed data query and computing engine. Familiarity with at least one scripting language: R, Python, or Scala Experience deploying machine learning systems using AWS, GCP, Virtual Machines, or Docker. Experience developing customizable, modular, and scalable deep learning algorithms in Keras/Pytorch/Tensorflow Research and design creative approaches to ambiguous problems, aiding in the implementation and scaling of these cutting edge systems Good tracking record on collaborating with business and engineering team on long-term projects, pushing excellence in the rest of the data science organization Have good understandings of statistical theory, distributions, experimental design, multivariable calculus, linear algebra, and how computational algorithms work

Skills required:
Hypothesis driven – uses data to test ideas rigorously and objectively Willing to teach and mentor colleagues Eager to stay on the cutting edge of methodologies and technologies

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