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X Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Mountain View, CA, USA; New York, NY, USA.
Minimum qualifications: - Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
- 4 years of experience in data analysis or data science, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
Preferred qualifications: - Ability to present to executives with clear communication, with a demonstrated track record of cross-functional stakeholder management and leadership through influence.
About the jobArtificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $232000 - $253000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Partner with product, engineering, and User Experience (UX) to develop data-driven product strategies.
- Translate ambiguous questions into well-defined problems, design experiments, and analyze large datasets for insights. Communicate findings and recommendations to stakeholders, including executives.
- Build and deploy statistical/ML models to understand our users, enhance product capabilities and personalize user experience.
- Advocate data-driven culture by feeding user engagement insights back into models.
- Collaborate with the GenAI team on model quality and feature adoption.
