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ID Peranan
205806
Jenis Pekerja
Regular Employee
Studio/Jabatan
Other
Pengaturan Kerja Fleksibel
Off Site

Perihalan & Keperluan

Kami adalah pasukan global yang terdiri daripada pencipta, pencerita, ahli teknologi, pembida pengalaman, inovator dan ramai lagi. Kami percaya bahawa permainan dan pengalaman yang menakjubkan bermula dengan pasukan yang pelbagai seperti pemain serta komuniti yang kami layani. Di Electronic Arts, hanya imaginasi yang menjadi batasan anda.

Empowering players to create is an exciting future for the gaming industry.  At Electronic Arts we have many examples of players creating content, whether it be a skateboard park in Skate or fantastical mansions in the Sims 4. The future definitely has our players being more empowered to create with their imagination being the only limit.

We are looking for a Data Scientist to help shape the future of content creation and gameplay with AI.  If you have the right expertise and are interested we want to hear from you!

As a Senior AI Data Scientist you will: 

  • Build, fine-tune and implement AI and machine learning models to solve challenging problems
  • Ensure AI and machine learning production pipelines are scalable, repeatable and cloud agnostic
  • Apply current and emerging techniques in deep learning, natural language processing and other machine learning areas
  • Collect, clean, manage, analyze and visualize large sets of data using multiple data platforms, tools and technique
  • Work in partnership with game teams to integrate AI solutions into products and services.
  • Optimize and fine-tune AI models for performance and scalability. Analyze and interpret data to extract meaningful insights and improve AI models. 
  • Document and present findings and solutions to stakeholders. 

Desired qualifications and experience:

  • A minimum of 3+ years of experience in data science
  • PhD or MSc in statistics, mathematics, computer science, or related field
  • Strong expertise in deep learning, fluent in Python and SQL
  • Expertise in automating machine learning models and building end to end products
  • Experience with devops tools and principles (Git, CI/CD, Docker)
  • Effective within Cloud environments (GCP, AWS)
  • Understanding of containerization and orchestration technologies (Docker, Kubernetes, etc.)