Data Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

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. That's why we employ the most creative, passionate people in the industry.

The Challenge Ahead:

As a curious Data Scientist, your background in applied Machine Learning (ML) has translated into commercially viable data products. You will report to the Senior Program Manager in Quality and Verification Solutions Analytics(QVSA) team. Your first assignment will be to lead the Defect Prevention initiative. You'll provide value partnering with the Quality Engineering team by implementing smart automation at scale.

• You will work with multiple partners to understand their domain, and create data science products to solve for their use cases and assist them in making important decisions.
• Translate business and product questions into ethical and mathematically sound experiments.
• Communicate data science projects and products to a broad audience, including a nontechnical audience.
• Ensure methodology and experimental design are used to produce applicable solutions.
• Build data manipulation, processing, and data visualizations to aid in your modelling efforts.
• Use your statistical and computational knowledge to build algorithms for calculating variances, state predictions, and find trends.
• Support peers with technical reviews, ensuring quality coding and deployment practices.

Requirements

• MS or greater in a field such as Mathematics, Computer Science, Economics, Statistics.
• 3 or more years of experience in data science creating data products at scale using AWS or other tools.
• SQL skills, including experience querying complex data sets such as platforms like Apache Hive.
• Experience developing statistical and machine learning models using languages like Python, R, or Ruby.
• Experience with experimental design and the determination of the statistical significance of findings.
• Knowledge of programming best practices, version control, and automation.
• Experience presenting and prioritizing with people at multiple levels of business and technical expertise.