Google DeepMind's GeminiApp team is on a mission to build a universal AI assistant that will empower billions of people by creating a personal, proactive, and powerful life assistant that will be used multiple times a day to increase productivity and creativity by 10 to 100-fold. The Data Scientist will be instrumental in building this assistant by ensuring strategic decisions are grounded in data and will use data to produce insights on emerging trends across GeminiApp and its competitors, influencing decision-making at the VP+ levels.
Requirements
- 5 years of experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems), and coding (e.g., Python, R, SQL) or 2 years of experience with a Master's degree.
- Proven experience in identifying data-driven opportunities for business/product improvement and defining/measuring the success of those initiatives
- Proven experience in setting up, maintaining, and reporting on top-line product performance and business metrics
- Experience with experimental design and analysis
- Experience working with large and messy datasets to solve ambiguous business problems
Responsibilities
- Analyze large complex datasets to produce concise, actionable insights
- Develop, implement, and track top-level product and business metrics
- Dive into metric developments and changes, and identify key drivers and root causes
- Automate currently manual metric reporting flows and outputs
- Build and deploy statistical/ML models to understand our users and product capabilities
- Partner with product, engineering, and UX to develop data-driven product insights and strategies
- Champion data-driven culture by feeding user engagement insights back into models
Other
- Translate ambiguous questions into well-defined problems
- Communicate findings and recommendations to executive stakeholders, including visualizing data in a clear, compelling way
- Strong communication, writing, and presentation skills
- Past experience on a performance or growth data science or similar team
- Ability to self-start and self-direct work in an unstructured, fast-paced, challenging environment
- A bias for action and creative problem-solving and ability to work effectively across functions and PAs
