About the Team
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.
About the Role
As a Data Scientist lead on the GeminiApp team, you are a key partner and co-creator in our product strategy while managing a growing team. 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.
What You’ll Do
- Partner with PM, engineering, and UX leadership to develop data-driven product strategies across various areas of GeminiApp
- Translate ambiguous questions into well-defined problems, design experiments, and analyze large complex datasets for insights
- Develop and implement novel, goal-oriented metrics
- Build and deploy statistical/ML models to understand our users, enhance product capabilities and personalize user experience
- Communicate findings & recommendations to stakeholders, including executives
- Champion data-driven culture by feeding user engagement insights back into models
- Collaborate with the GenAI team on model quality and feature adoption
- Act as a technical leader for a global team, guiding junior members on complex analyses and upholding best practices to ensure high-quality, impactful work
What We're Looking For
- A bias for action and a relentless drive to build something great. You are a resourceful and creative problem-solver, able to find innovative solutions in a fast-paced and dynamic environment. You are comfortable with ambiguity and thrive on a challenge.
- Strong business acumen and a strategic mindset. You have a proven ability to connect data-driven insights to business impact and can effectively translate business needs into data science problems.
- Deep technical expertise. You have a strong foundation in statistical modeling, machine learning, and experimental design. You are proficient in SQL and have hands-on experience with a programming language like Python or R.
- Exceptional communication and presentation skills. You can articulate complex technical concepts to both technical and non-technical audiences, including executive leadership. You are a compelling storyteller who can use data to influence decisions.
- A collaborative and influential partner. You have a track record of successfully collaborating with and influencing cross-functional teams, particularly engineering and product management, to drive data-informed decisions. You are ready to work in an environment with a shared roadmap that holds multiple teams accountable for both model quality and feature adoption.
- A commitment to user trust and privacy. You understand the importance of telling users what data is being used and why, and you are committed to providing users with granular, easy-to-understand controls over their personal information.
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.
You must meet these minimum qualifications to apply for this job
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Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
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10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.
Having as many of these specific qualifications is a plus, but transferable skills/experiences may be equally valuable
- Graduate degree in Statistics, Computer Science, Engineering or Mathematics.
- Familiarity with modern Machine Learning and LLM techniques
- Strong organization and prioritization skills along with outstanding written and verbal communication skills.
- Strong data science coding skills in Python, R, SQL or related languages
- Experience articulating business questions and using mathematical techniques to arrive at an answer using available data.
- Experience translating analysis results into business recommendations.
- Proven experience delivering bespoke analytics to senior stakeholders (problem scoping/definition, modeling, interpretation, presentation)
The US base salary range for this full-time position is between $248,000 USD - 349,000 USD + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.
Application deadline: 28 February 2026
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 ourApplicant 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.