Senior UX Quantitative Researcher, Google Maps

📍 Job Overview

Job Title: Senior UX Quantitative Researcher, Google Maps

Company: Google

Location: New York, NY; Seattle, WA; San Francisco, CA

Job Type: Full-time

Category: User Experience Research (Quantitative)

Date Posted: 2026-06-18T17:09:12.635

Experience Level: 6+ years (Minimum), 5+ years (Preferred with postgraduate degree)

Remote Status: On-site

🚀 Role Summary

• Lead high-impact quantitative research programs for Google Maps, focusing on user behavior analysis and product quality measurement.

• Drive innovation in scaled methodologies, leveraging logs analysis, survey design, and statistical modeling to inform product strategy.

• Collaborate with cross-functional teams including Engineering, Product Management, and Data Science to influence product roadmaps and key user metrics.

• Contribute to the advancement of AI models and user experience through data-friendly instrumentation and taxonomy development.

• Mentor junior and mid-level quantitative UXRs, fostering a collaborative and high-performing research community.

📝 Enhancement Note: This role is positioned within the Google Geo UX organization, indicating a significant focus on large-scale, strategic research initiatives with high leadership visibility. The emphasis on "horizontal programs" suggests influencing across multiple product areas within Google Maps and potentially related Geo products.

📈 Primary Responsibilities

• Lead the design, execution, and analysis of large-scale quantitative research programs across Google Maps, utilizing methods such as logs analysis, experimental design, and survey research.

• Develop and refine scaled survey methodologies and AI-driven tooling to accurately measure product quality and user satisfaction at scale.

• Define and implement analysis-friendly instrumentation and taxonomy to enhance AI model development and improve user experience insights.

• Provide expert mentorship and guidance to junior and mid-level quantitative UXRs, fostering best practices in research design and execution.

• Partner closely with Engineering, Product Management, and Data Science teams to translate research findings into actionable product strategies, influence roadmaps, and establish key launch metrics.

• Drive innovation in quantitative research practices, seeking out and implementing new methodologies and tools to enhance research rigor and impact.

• Communicate complex research findings and strategic recommendations clearly and effectively to executive leadership and cross-functional stakeholders.

📝 Enhancement Note: The responsibilities highlight a blend of hands-on research execution and strategic leadership. The emphasis on "elevate the excellence and standardization of research practices" and "driving innovation" suggests a role that not only executes research but also shapes the future of quantitative UXR within Google Maps.

🎓 Skills & Qualifications

Education:

• Bachelor's degree in a relevant field (e.g., Computer Science, Statistics, Psychology, Human-Computer Interaction) or equivalent practical experience.

• Master's degree or PhD in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, or a related field is preferred. Experience:

• Minimum of 6 years of experience in applied product research or a similar quantitative research setting.

• Preferred candidates will have 5 years of experience conducting UX research on products and working directly with executive leadership (Director level and above).

• 3 years of experience managing projects and operating within large, matrixed organizations is preferred. Required Skills:

• Proficiency in programming languages for data manipulation and computational statistics (e.g., Python, R, MATLAB, C++, Java, or Go).

• Strong experience in logs analysis to understand user behavior patterns from product usage data.

• Expertise in survey design, including question formulation, sampling strategies, and survey platform management.

• Demonstrated experience in statistical analysis, including regression analysis, hypothesis testing, and experimental design.

• Proficiency in metrics development and defining key performance indicators (KPIs) for product success.

• Experience with empirical methods for investigating user behavior. Preferred Skills:

• Experience designing, testing, and analyzing large-scale in-product surveys.

• Proven ability to set up quantitative programs and align outcomes against user metrics.

• Familiarity with Human-Computer Interaction (HCI) principles and methodologies.

• Experience in a large, matrixed organization with complex stakeholder management.

• Skills in data visualization and dashboard creation for communicating insights.

📝 Enhancement Note: The requirements emphasize a strong technical foundation in programming and statistics, combined with practical experience in product research. The preferred qualifications suggest a candidate who can operate at a senior level, influencing strategy and managing complex projects within a large corporate structure.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case Studies: Showcase detailed case studies of quantitative research projects led, demonstrating the research question, methodology (logs analysis, surveys, experiments), execution, and impact.

• Methodological Depth: Highlight expertise in designing and implementing complex surveys, analyzing large datasets from logs, and applying statistical modeling techniques.

• Instrumentation & Taxonomy: Provide examples of contributions to developing data instrumentation or taxonomy that improved the quality of quantitative data for analysis.

• Impact & Influence: Clearly articulate how your research findings influenced product strategy, decision-making, and key product metrics, ideally with quantifiable results.

• Tool Proficiency: Demonstrate practical application of programming languages (Python, R, etc.) and statistical analysis tools within research projects.

Process Documentation:

• Research Design & Planning: Examples of how you've structured and planned large-scale quantitative research initiatives, including stakeholder alignment and resource allocation.

• Data Analysis & Interpretation: Showcase your approach to analyzing complex datasets, identifying key insights, and drawing robust conclusions.

• Methodology Innovation: Document instances where you've proposed or implemented novel quantitative research methods or tools to overcome specific challenges.

• Cross-functional Collaboration: Illustrate your process for working with engineering, product management, and data science, ensuring research is integrated effectively into the product development lifecycle.

📝 Enhancement Note: Given the role's focus on leading programs and influencing strategy, a portfolio should emphasize not just individual research execution, but also program management, methodological innovation, and the tangible impact of research on product outcomes and organizational practices.

💵 Compensation & Benefits

Salary Range: $159,000 - $231,000 USD per year.

Benefits:

• Bonus Target: An annual bonus target of 15% of base salary, tied to individual and company performance.

• Equity: Stock options or restricted stock units (RSUs) as part of the total compensation package.

• Comprehensive Benefits: Includes health insurance (medical, dental, vision), retirement savings plans (e.g., 401k), paid time off, parental leave, and other employee wellness programs.

• Professional Development: Access to internal learning resources, mentorship programs, and opportunities for skill enhancement.

Working Hours:

• Typically 40 hours per week, with flexibility often available based on project needs and team agreements. The on-site nature suggests core business hours are expected for collaboration.

📝 Enhancement Note: The salary range provided is for the US market, specifically for New York, Seattle, and San Francisco, which are high cost-of-living areas. The range reflects a senior-level position at a major tech company like Google, considering the required experience, specialized skills, and the role's strategic importance. The bonus and equity components are standard for such senior roles in the tech industry.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology (Internet Services and Software)

Company Size: Large Enterprise (Google is part of Alphabet Inc., employing over 180,000 people globally).

Founded: 1998 (Google). The company has a long-standing history of innovation and user-centric product development.

Team Structure:

• Geo UX Organization: This role sits within the Google Geo UX organization, which is dedicated to building the most accurate, comprehensive, and useful mapping products (Maps, Earth, Street View, etc.).

• Cross-functional Integration: The Quant UXR will be embedded within multi-disciplinary teams, collaborating closely with Engineering, Product Management, and Data Science. This structure emphasizes shared ownership and data-driven decision-making.

• Reporting Hierarchy: Likely reports to a Senior Manager or Director of UX Research within the Geo organization, with potential for matrixed reporting on specific project initiatives.

Methodology:

• User-Centric Approach: Google's core philosophy, "Focus on the user and all else will follow," drives all product development and research efforts. Quantitative research is crucial for understanding user behavior at scale.

• Data-Driven Decision Making: Emphasis on empirical methods like logs analysis, surveys, and statistical modeling to provide objective insights that inform product strategy and design.

• Innovation and Scalability: A drive to develop new methodologies, leverage AI-driven tooling, and create scalable solutions for measuring product quality and user experience across massive user bases.

Company Website: https://www.google.com

📝 Enhancement Note: Google's culture is known for its data-driven approach, emphasis on innovation, and a strong focus on user needs. The Geo UX team specifically deals with complex geospatial data and aims to provide highly reliable and useful mapping experiences for a global audience, requiring rigorous quantitative validation.

📈 Career & Growth Analysis

Operations Career Level: Senior Individual Contributor (IC). This role is for a seasoned researcher who can lead complex projects independently and mentor others. It represents a significant step beyond mid-level research roles, requiring strategic thinking and leadership.

Reporting Structure: The role reports into the Geo UX organization, likely to a Research Manager or Director. Close collaboration with Product Managers and Engineering Leads is expected, providing exposure to product strategy and development cycles.

Operations Impact: The quantitative research conducted directly influences the evolution of Google Maps, a flagship product used by over a billion people monthly. Findings from this role will shape product strategy, prioritize feature development, and ensure the highest standards of user experience and product quality are met. This role has the potential for significant impact on a globally used product.

Growth Opportunities:

• Strategic Leadership: Opportunity to lead major horizontal research programs with high executive visibility, shaping the future direction of quantitative research within Google Geo.

• Methodological Advancement: Chance to drive innovation in scaled survey methodologies, AI-driven tooling, and advanced statistical modeling, contributing to the broader field of UX research.

• Mentorship & Community: Develop leadership skills through mentoring junior researchers and actively participating in the internal Quant UXR community, sharing knowledge and best practices.

• Specialization: Potential to deepen expertise in specific areas of quantitative research, such as large-scale survey design, causal inference, or AI-driven user insights.

• Career Progression: Pathways can lead to Principal UX Researcher roles, research management, or transitions into related product strategy or data science leadership positions within Google.

📝 Enhancement Note: This role offers substantial growth potential for a researcher who excels in quantitative methodologies and can translate complex data into strategic product direction. The emphasis on mentorship and community engagement also provides avenues for developing leadership and soft skills crucial for career advancement.

🌐 Work Environment

Office Type: Google offices are typically modern, open-plan environments designed to foster collaboration and innovation. They are equipped with amenities to support employee well-being and productivity.

Office Location(s): This position is available on-site in Google's major tech hubs: New York, NY; Seattle, WA; and San Francisco, CA. These locations offer vibrant urban environments with access to talent and industry events.

Workspace Context:

• Collaborative Spaces: Access to meeting rooms, brainstorming areas, and informal gathering spots designed for team collaboration and cross-functional discussions.

• Technology & Tools: Employees have access to Google's powerful internal tools, robust computing resources, and a comprehensive software suite supporting research, analysis, and communication.

• Team Interaction: Regular opportunities for direct interaction with research peers, product managers, engineers, and designers, encouraging a dynamic and integrated work environment.

• On-Site Culture: Expect a culture that values in-person collaboration, spontaneous idea sharing, and team-building activities.

Work Schedule:

• Standard 40-hour work week with an on-site requirement. While core hours are expected for team collaboration, Google often offers some flexibility in daily scheduling, provided project deliverables are met and team syncs are attended.

📝 Enhancement Note: The on-site requirement in major tech hubs indicates a preference for collaborative, in-person work. This is common for roles that involve deep cross-functional integration and require leveraging shared resources and spontaneous ideation.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter will review your application and may conduct an initial phone screen to assess basic qualifications and interest.

• Recruiter Screen: A more in-depth conversation with a recruiter focusing on your experience, motivations, and alignment with the role and Google's culture.

• Hiring Manager Interview: A discussion with the hiring manager, likely focusing on your past research projects, leadership experience, and strategic thinking.

This is where your portfolio will be a key discussion point.

• Technical/Research Interviews: Expect multiple interviews with peers and senior researchers. These will likely involve:

  • Portfolio Review: Presenting 1-2 key projects from your portfolio, detailing your role, methodology, findings, and impact. Be prepared to discuss challenges and trade-offs.
  • Methodology Deep Dive: Questions testing your knowledge of quantitative research methods, statistical concepts, and your ability to apply them to specific product scenarios.
  • Problem-Solving/Case Study: You might be given a hypothetical product problem and asked to outline how you would approach researching it quantitatively.

• Cross-Functional Interview: An interview with a partner from Product Management or Engineering to assess your collaboration style and ability to influence stakeholders.

• "Googlyness" / Behavioral Interview: Assessing cultural fit, teamwork, problem-solving approach, and alignment with Google's values.

Portfolio Review Tips:

• Curate Selectively: Choose 2-3 of your most impactful quantitative research projects that best showcase your skills for this specific role.

• Structure for Impact: For each project, clearly articulate:

  • The business/product problem.
  • Your specific role and contributions.
  • The quantitative methodology used (logs analysis, survey design, experimental design, etc.).
  • Key findings and insights.
  • The impact of your research on product decisions or outcomes (quantify where possible).
  • Any challenges faced and how you overcame them.

• Quantify Everything: Emphasize metrics, statistical significance, and ROI where applicable.

• Demonstrate Leadership: Highlight instances where you led research programs, mentored others, or influenced product strategy.

• Prepare Your Narrative: Be ready to walk through your portfolio confidently and answer detailed questions about your process and decision-making. Use slides or a digital format that is easy to follow.

Challenge Preparation:

• Think Like a Product Leader: When presented with a hypothetical problem, focus on understanding the user and business goals first.

• Outline Your Approach: Clearly define the research questions, target user segments, chosen methodologies, key metrics to track, and potential challenges.

• Justify Your Choices: Be prepared to explain why you chose a particular method over others, considering trade-offs in time, resources, and validity.

• Consider Scale: For Google Maps, always think about how your research approach scales to a global user base and large datasets.

📝 Enhancement Note: Google interviews are rigorous and focus on assessing both technical/methodological skills and behavioral/cultural fit. A strong, well-prepared portfolio is critical for demonstrating your expertise and impact.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python (with libraries like Pandas, NumPy, SciPy, Statsmodels), R (with tidyverse, lme4, etc.). Experience with MATLAB, C++, Java, or Go may also be relevant.

• Statistical Software: Proficiency with statistical packages and libraries for analysis, modeling, and hypothesis testing.

• Data Analysis & Visualization Tools: Tools for data manipulation, exploration, and creating clear visualizations (e.g., internal Google tools, potentially Tableau, Looker, or similar).

Analytics & Reporting:

• Logs Analysis Platforms: Experience with tools or scripting for analyzing large-scale user interaction logs.

• Survey Platforms: Familiarity with internal or external survey tools for designing, deploying, and collecting data from large user samples.

• Data Warehousing/Querying: SQL or similar for accessing and manipulating data from large databases.

CRM & Automation:

• While not a direct CRM role, understanding how user data flows from product interactions into broader systems for analysis and reporting is beneficial.

• Familiarity with experimental design frameworks and potentially A/B testing platforms for measuring impact.

📝 Enhancement Note: The emphasis on Python and R, along with logs analysis and survey design, indicates a need for a technically proficient researcher who can handle complex data pipelines and statistical modeling. Google heavily relies on its internal tooling, so adaptability and a strong foundational understanding of data manipulation and statistics are key.

👥 Team Culture & Values

Operations Values:

• User Focus: A deep commitment to understanding and serving the user, ensuring that research directly contributes to improving their experience.

• Data-Driven Rigor: A strong emphasis on empirical evidence, statistical validity, and methodological soundness in all research endeavors.

• Innovation & Impact: A drive to push the boundaries of research methodologies, develop novel solutions, and ensure research has a tangible, positive impact on products.

• Collaboration & Transparency: A culture that values open communication, constructive feedback, and close partnerships across disciplines to achieve shared goals.

• Scalability & Efficiency: A focus on developing methods and tools that can be applied effectively across Google's massive user base.

Collaboration Style:

• Cross-functional Partnership: Researchers are expected to work seamlessly with Product Managers, Engineers, Designers, and Data Scientists, acting as a bridge between user needs and product development.

• Proactive Communication: Regularly sharing insights, seeking feedback, and aligning on research plans and methodologies with stakeholders.

• Knowledge Sharing: Active participation in internal research communities, sharing best practices, learnings, and contributing to the collective knowledge base of quantitative UX research at Google.

📝 Enhancement Note: Google's culture highly values individuals who are both technically excellent and strong collaborators. For this role, demonstrating an ability to translate complex quantitative findings into actionable product insights and influence diverse stakeholders is paramount.

⚡ Challenges & Growth Opportunities

Challenges:

• Scale of Data: Analyzing and interpreting massive datasets from Google Maps users globally presents unique computational and analytical challenges.

• Methodological Innovation: Continuously advancing scaled survey methodologies and AI-driven tooling to maintain research rigor and efficiency in a rapidly evolving landscape.

• Influencing Product Strategy: Effectively translating complex quantitative findings into clear, actionable recommendations that influence high-stakes product decisions with senior leadership.

• Cross-functional Alignment: Ensuring research objectives and findings are understood and acted upon by diverse teams (Engineering, PM, Data Science) with different priorities.

• Defining "Product Quality": Developing robust metrics and taxonomies to objectively measure and improve the multifaceted concept of product quality for a complex product like Google Maps.

Learning & Development Opportunities:

• Advanced Methodologies: Opportunity to work with cutting-edge quantitative research techniques, AI-powered insights tools, and large-scale experimentation.

• Industry Exposure: Access to internal Google conferences, workshops, and potentially external industry events to stay abreast of the latest trends in UX research and data science.

• Mentorship Programs: Formal and informal mentorship opportunities within the strong Quant UXR community at Google, providing guidance on technical skills, career development, and navigating large organizations.

• Leadership Development: Taking on lead roles in major research programs to hone project management, strategic planning, and stakeholder influence skills.

• Cross-pollination: Exposure to diverse product areas within Google Geo, broadening understanding of different user needs and market dynamics.

📝 Enhancement Note: This role provides a platform to tackle some of the most challenging problems in large-scale user research. Success will come from a combination of technical expertise, strategic thinking, and the ability to adapt and innovate in a fast-paced environment.

💡 Interview Preparation

Strategy Questions:

• "Tell me about a time you led a large-scale quantitative research program. What was the goal, your methodology, the key findings, and the impact on the product?" (Prepare a detailed STAR method response focusing on your leadership, methodological rigor, and quantifiable impact.)

• "How would you approach measuring the 'quality' of a new feature in Google Maps, considering millions of users?" (Focus on defining key metrics, identifying data sources like logs and surveys, and outlining an experimental design.)

• "Describe a situation where your quantitative findings challenged the existing product direction. How did you present this information and influence stakeholders?" (Highlight your communication skills, data storytelling, and ability to navigate difficult conversations.) Company & Culture Questions:

• "Why Google? And why Google Maps specifically?" (Research Google's mission, values, and the impact of Google Maps. Connect your passion for user-centric research and large-scale impact to these.)

• "How do you approach mentoring junior researchers?" (Discuss your philosophy on guiding others, providing constructive feedback, and fostering growth.)

• "How do you ensure your research is unbiased and objective?" (Discuss your awareness of potential biases in survey design, sampling, and analysis, and how you mitigate them.) Portfolio Presentation Strategy:

• Focus on Impact: For each case study, clearly articulate the business problem, your research question, the methodology, your specific contribution, the key insights, and the measurable impact on the product or business.

• Quantify Results: Use numbers, percentages, and statistical significance wherever possible to demonstrate the rigor and impact of your work.

• Explain Your "Why": Be prepared to justify your methodological choices, discuss trade-offs, and explain the reasoning behind your analysis and recommendations.

• Showcase Leadership: Highlight instances where you took initiative, mentored others, or drove strategic direction through your research.

• Keep it Concise: Practice your presentation to ensure it fits within the allotted time, typically 30-45 minutes for the portfolio review itself. Be ready for follow-up questions.

📝 Enhancement Note: Google interviews are designed to assess your problem-solving skills, technical depth, and cultural fit. Demonstrating a proactive, data-driven, and user-centric approach, coupled with strong communication and collaboration abilities, will be key to success.

📌 Application Steps

To apply for this Senior UX Quantitative Researcher position:

• Submit your application through the Google Careers portal via the provided link.

• Portfolio Customization: Tailor your resume and portfolio to highlight your most relevant quantitative research experience, focusing on logs analysis, scaled surveys, statistical modeling, and product strategy influence. Ensure your portfolio showcases projects with measurable impact.

• Resume Optimization: Clearly articulate your experience with specific programming languages (Python, R), statistical analysis techniques, and experience in applied product research. Use keywords from the job description naturally.

• Interview Preparation: Practice answering behavioral and situational interview questions using the STAR method. Prepare to present 1-2 key portfolio projects in detail, focusing on your role, methodology, findings, and impact.

• Company Research: Familiarize yourself with Google's mission, values, and the specific goals and challenges of the Google Maps product. Understand Google's approach to user research and data-driven decision-making.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.