Senior Data Scientist, GeminiApp, Ecosystems

DeepMind • Mountain View, CA

46d

About The Position

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. Our team, GeminiApp, is on a mission to build a universal AI assistant that will empower billions of people. We are 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. Our work is shaping how humanity interacts with AI at scale. As a Data Scientist on the GeminiApp team, you are a key partner and co-creator in our product strategy. You will be instrumental in building a uniquely proactive and powerful assistant by ensuring our strategic decisions are grounded in data. This is a high-impact role for a data scientist who is excited about working in a fast-paced, innovative environment and who is passionate about building user-centered experiences that will redefine our relationship with technology. As part of the Ecosystem Data Science team, you will use data to produce insights on emerging trends across all of GeminiApp and our competitors. Your work will be highly visible and highly impactful: this team's output regularly influences decision-making at the VP+ levels.

Requirements

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 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.
• 2 years of work experience identifying opportunities for business/product improvement and then defining/measuring the success of those initiatives.

Nice To Haves

• 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
• Strong communication, writing, and presentation skills
• Past experience on a performance or growth data science or similar team
• Experience with experimental design and analysis
• Experience working with large and messy datasets to solve ambiguous business problems
• 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

Responsibilities

• Translate ambiguous questions into well-defined problems
• Analyze large complex datasets to produce concise, actionable insights
• Communicate findings and recommendations to executive stakeholders, including visualizing data in a clear, compelling way
• 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

Benefits

• You'll have a direct and meaningful impact on a product designed to empower billions of people and be one of the greatest forces for good in the world.
• We're a fast-growing team within Google, and you'll have the opportunity to evolve quickly to meet changing user needs.
• You'll work with a talented and passionate team of people who are excited about what they do and have fun doing it.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Publishing Industries