招聘
About the job
At Google, we "Focus on the user and all else will follow." As a Quantitative User Experience Researcher (Quant UXR), you make this possible. You will join a multi-disciplinary team, collaborating closely with Engineering and Product Management to create industry-leading, innovative products.
You will drive impact at all stages of development by investigating user behavior through empirical methods like log analysis, survey research, and regression. We value various educational experiences—from Computer Science to Psychology—and require a blend of behavioral research design, statistical proficiency, and programming skills to uncover actionable insights. Beyond the work, you will grow within a supportive Quant UXR community offering mentorship, regular meetups, and exclusive internal tools to help you thrive.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve engineering issues and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
The US base salary range for this full-time position is $189,000-$274,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
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Influence stakeholders across organizations to gain support for research-based, user-centric solutions.
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Manage project priorities in alignment with product goals, and oversee allocation of resources within the project.
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Drive ideas to improve products and services through research-driven insights and recommendations.
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Lead teams to define and evaluate product, service, and ecosystem impact.
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Own idea and strategy discussions through research by analyzing, consolidating, or synthesizing what is known about user, product, service, or business needs.
Minimum qualifications
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Bachelor’s degree or equivalent practical experience.
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8 years of experience in an applied research setting, or similar.
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Experience in programming languages used for data manipulation and computational statistics (e.g., Python, R, MATLAB, C++, Java, or Go).
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Experience building and shipping products powered by Machine Learning, Natural Language Processing (NLP), or Large Language Models (LLMs).
Preferred qualifications
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Master's degree or PhD in human-computer interaction, cognitive science, statistics, psychology, anthropology, or a related field.
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8 years of experience conducting UX research on products.
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7 years of experience working with executive leadership.
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5 years of experience managing projects, and working in a changing organization.
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Experience working in close partnerships with teams developing or training Generative AI products and models.
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关于Google

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
员工数
Mountain View
总部位置
$1,700B
企业估值
评价
3.7
25条评价
工作生活平衡
3.8
薪酬
4.2
企业文化
3.4
职业发展
3.9
管理层
2.8
68%
推荐给朋友
优点
Excellent compensation and benefits
Smart and talented colleagues
Great perks and work flexibility
缺点
Management and leadership issues
Bureaucracy and slow processes
Constantly changing priorities and reorganizations
薪资范围
57,502个数据点
Junior/L3
L3
L4
L5
L6
L7
L8
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Junior/L3 · Data Scientist L3
0份报告
$176,704
年薪总额
基本工资
-
股票
-
奖金
-
$150,298
$203,110
面试经验
9次面试
难度
3.4
/ 5
时长
14-28周
录用率
44%
体验
正面 0%
中性 56%
负面 44%
面试流程
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
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