Data Scientist, GeminiApp, Ecosystems at DeepMind

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

30 Jan, 26

Salary

229000.0

Posted On

01 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analysis, Statistical Analysis, Python, R, SQL, Data Visualization, Machine Learning, Product Metrics, Business Improvement, Communication, Experimental Design, Problem Solving, User Engagement, Data-Driven Insights, Collaboration, Self-Directed Work

Industry

Research Services

Description

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 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. Key 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 About You In order to set you up for success as a Data Scientist at Google DeepMind, we look for the following skills and experience: 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. In addition, the following would be an advantage: 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 Why You'll Love Working Here Impact: 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. Growth: We're a fast-growing team within Google, and you'll have the opportunity to evolve quickly to meet changing user needs. Team & Culture: You'll work with a talented and passionate team of people who are excited about what they do and have fun doing it. The US base salary range for this full-time position is between $156,000- $229,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process. Application deadline: November 14, 2025 Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Responsibilities

As a Data Scientist, you will analyze large datasets to produce actionable insights and communicate findings to executive stakeholders. You will also develop and track product and business metrics while automating reporting flows.