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Snapshot

You are a data QA analyst with a passion for ensuring data quality and a dedicated, can-do, attitude to overcoming technical and process challenges. To succeed in this role you will have professional experience working with data as a quality assurance expert.

About Us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The Role

As a data QA analyst, you will join a highly collaborative team of QA experts. This role is vital in ensuring the quality and reliability of our data, directly impacting cutting-edge AI research and development.  Your expertise in quality assurance will be essential to the success of our projects.

Key responsibilities:

  • Generating cross functional reports based on your analysis of data, focusing on uncovering patterns, anomalies, and quality problems.  
  • Ensuring the continuous delivery of high-quality data used in groundbreaking AI research and development
  • Collaborating with a variety of disciplines from engineers, research and data scientists to ensure research and quality requirements are met.
  • Taking complex concepts and generating clear and concise training materials for data collections.
  • Reviewing and providing feedback on UX/UI elements for our internal tools.
  • Contributing to the development and improvement of quality processes and best practices.

About You

In order to set you up for success as a Data QA Analyst at Google DeepMind,  we look for the following skills and experience:

  • Ability to work and communicate well with diverse groups of people with different requirements and ways of working.
  • Experience in quality assurance.
  • Passionate about building tools to improve QA workflows.
  • Can communicate ideas effectively.
  • Can thrive and adapt in a rapidly changing, highly-agile environment.
  • Are proactive in identifying critical problems and generating and driving solutions.

In addition, the following would be an advantage: 

  • Python knowledge
  • Experience in data science or data quality
  • Understanding of machine learning concepts in data quality assessment
  • Familiarity with version control systems

Application deadline: 20th January 2025

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