Senior Quantitative UX Researcher, Wear OS at Google

📍 Job Overview

Job Title: Senior Quantitative UX Researcher, Wear OS
Company: Google
Location: London, England, United Kingdom
Job Type: Full-time
Category: User Experience (UX) Research / Data Analysis
Date Posted: 2025-07-22T14:00:44.891
Experience Level: 5-10 Years
Remote Status: On-site

🚀 Role Summary

This role is pivotal in shaping the user experience of Google's Wear OS by leveraging advanced quantitative research methodologies and data analysis to inform product strategy and design.
You will be responsible for defining, measuring, and analyzing key user experience metrics, translating complex data sets into actionable insights that drive product improvements and innovation.
The position requires a strong foundation in statistical methods, programming for data manipulation, and a collaborative approach to influence product decisions alongside cross-functional teams.
Success in this role hinges on your ability to conduct rigorous empirical research, identify user behavior patterns, and effectively communicate findings to diverse stakeholders, ultimately enhancing the usability and delight of products for billions of users.

📝 Enhancement Note: While the primary focus is UX Research, the emphasis on quantitative methods, data manipulation, statistical modeling, and programming (Python, R, SQL) strongly aligns with the analytical and data-driven aspects of Revenue Operations and Sales Operations roles, particularly in understanding user behavior and optimizing processes for business impact.

📈 Primary Responsibilities

Define and measure quantitative UX goals and metrics in close collaboration with cross-functional partners including UX Designers, Qualitative Researchers, Data Scientists, Engineers, and Program Managers.
Develop and implement statistical models and code using languages like Python, R, or SQL to analyze user behavior, identify patterns, and extract actionable insights from large datasets.
Conduct empirical research utilizing methods from computer science, quantitative social science, statistics, econometrics, and other relevant fields to gain a deep understanding of user needs and behaviors.
Examine existing data sets and product designs to formulate hypotheses and design high-impact research studies that address critical user experience questions.
Prioritize and drive research initiatives to optimize user experience, ensuring that findings are communicated effectively and persuasively to stakeholders at all levels, including both research experts and non-experts.
Contribute to the entire product development lifecycle, from ideation and design to iteration and launch, by providing data-driven user insights.
Ensure strict adherence to all company health and safety policies, procedures, and legal requirements.

📝 Enhancement Note: The responsibility of defining and measuring quantitative UX goals and metrics, coupled with the need to conduct empirical research and analyze data, directly mirrors the core functions within Revenue Operations and Sales Operations, which focus on defining key performance indicators (KPIs), analyzing sales and revenue data, and driving process improvements based on data-driven insights.

🎓 Skills & Qualifications

Education:

Bachelor's degree in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, a related quantitative field, or equivalent practical experience.
Preferred: Master's degree or PhD in Human-Computer Interaction, Psychology, Political Science, Statistics, Computer Science, or a similar advanced quantitative or behavioral science discipline.

Experience:

Minimum of 5 years of experience in an applied research setting, product research, or a closely related field focused on quantitative analysis and user behavior.
Preferred: Experience collaborating effectively with interdisciplinary teams, including product managers, designers, and engineers, to translate research findings into tangible product improvements and influence product strategy.

Required Skills:

Proficiency in survey design, including best practices for question formulation, sampling, and scale development, as well as experience in metrics development for user experience.
Strong experience in programming languages commonly used for data manipulation and computational statistics, such as Python, R, and SQL, to extract, clean, and analyze complex datasets.
Demonstrated ability to conduct quantitative user research using empirical methods, including log analysis, survey research, path modeling, and regression analysis.
Experience in cleaning, joining, and analyzing diverse datasets, including logs, surveys, and other forms of user interaction data.
Excellent quantitative research method skills necessary to produce robust insights and drive product excellence.

Preferred Skills:

Experience with data visualization techniques and tools (e.g., Tableau, Looker, D3.js) for creating compelling visual narratives and storytelling with data.
Proven ability to communicate complex research findings clearly and concisely to a wide range of stakeholders, influencing product decisions and driving adoption of user-centered design principles.
Understanding of statistical concepts and their application in behavioral research, including experimental design, hypothesis testing, and causal inference.

📝 Enhancement Note: The emphasis on quantitative research methods, data analysis proficiency (Python, R, SQL), survey design, and metrics development directly aligns with the skill sets required for operations professionals focused on performance analysis, process optimization, and data-driven decision-making within sales and revenue operations.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

Showcase a portfolio that clearly demonstrates your quantitative research capabilities, including examples of research design, data analysis, and the resulting impact on product development.
Highlight projects where you have defined and measured key user experience metrics, illustrating your ability to connect research to business objectives and product performance.
Include case studies demonstrating your experience in cleaning, joining, and analyzing complex datasets from various sources, showcasing your data wrangling and analytical rigor.
Present examples of how you've translated data insights into actionable recommendations that influenced product decisions and improved user experience, quantifying the impact where possible.

Process Documentation:

Provide documentation or descriptions of your systematic approach to designing and executing quantitative research studies, from initial problem definition to final reporting.
Detail your methodology for developing and validating quantitative metrics that accurately reflect user behavior and product success.
Showcase your process for data analysis, including the tools and techniques used, and how you ensure the validity and reliability of your findings.

📝 Enhancement Note: For operations roles, a portfolio would similarly focus on process optimization case studies, data analysis projects showing efficiency improvements, system implementation examples, and demonstrable ROI. The core requirement is showcasing analytical rigor and impact, which is transferable across disciplines.

💵 Compensation & Benefits

Salary Range:

Based on industry data for Senior Quantitative UX Researchers in London, UK, with 5-10 years of experience, typical salary ranges can be between £75,000 - £110,000 per annum. This estimate considers Google's compensation philosophy, which is generally competitive within the tech industry, and the specific market rate for specialized research roles in London.

Benefits:

Comprehensive health, dental, and vision insurance plans.
Generous paid time off, including vacation days, holidays, and sick leave.
Retirement savings plan with company matching contributions (e.g., Pension Scheme).
Professional development opportunities, including access to internal training, conferences, and educational resources.
Employee assistance programs and wellness initiatives.
Stock options or other equity-based compensation.
Parental leave and family-friendly benefits.
Commuter benefits and on-site amenities (depending on office location).

Working Hours:

Typically a 40-hour work week, with flexibility to accommodate project deadlines and research needs. The role is primarily on-site, requiring attendance at the London office.

📝 Enhancement Note: Senior operations roles in major tech hubs like London often command salaries in a similar range. Benefits packages are also typically robust, focusing on professional development, health and wellness, and long-term financial security, reflecting the value placed on experienced professionals.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology (Software & Hardware Development, Operating Systems)
Company Size: Very Large (100,000+ employees globally)
Founded: 1998

Team Structure:

The UX team at Google is a multi-disciplinary group comprising UX Designers, Researchers (both qualitative and quantitative), Writers, Content Strategists, Program Managers, and Engineers.
This role reports into a UX Research leadership structure, likely within the Wear OS product area, with direct collaboration across product management, engineering, and design functions.
Cross-functional collaboration is a cornerstone of Google's culture, encouraging close partnerships between researchers, designers, engineers, and product managers to ensure user needs are integrated throughout the product development lifecycle.

Methodology:

Data-driven decision-making is paramount, with a strong emphasis on empirical research and quantitative analysis to validate hypotheses and inform product direction.
Workflow planning and optimization are continuous processes, driven by user feedback, performance metrics, and iterative design testing.
Automation and efficiency practices are employed where applicable, but the core focus remains on deep user understanding derived from rigorous research.

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

📝 Enhancement Note: Google's culture is renowned for its data-centric approach, innovation, and emphasis on user focus. For operations professionals, this translates to an environment where process optimization, data analysis, and metric-driven improvements are highly valued and encouraged.

📈 Career & Growth Analysis

Operations Career Level: Senior Individual Contributor (IC)
Reporting Structure: The Senior Quantitative UX Researcher will likely report to a UX Research Manager or Lead within the Wear OS division. They will work collaboratively with Product Managers, UX Designers, Engineers, and potentially Data Scientists.
Operations Impact: This role has a direct impact on the success of Wear OS by ensuring that product development is guided by a deep understanding of user behavior and needs, ultimately influencing user adoption, satisfaction, and retention, which in turn drives business outcomes and revenue.

Growth Opportunities:

Operations Skill Advancement: Deepen expertise in advanced statistical modeling, machine learning for UX analysis, causal inference, and specific quantitative methodologies relevant to user behavior.
Leadership & Mentorship: Potential to mentor junior researchers, lead research initiatives for key product areas, and contribute to the broader UX research community within Google.
Cross-Functional Leadership: Transition into Product Management or specialized Data Science roles by leveraging a strong understanding of user needs and product strategy.
Specialization: Develop deep expertise in a specific area of Wear OS or in a particular quantitative research domain.

📝 Enhancement Note: The growth trajectory for experienced operations professionals often involves specializing in areas like sales analytics, revenue forecasting, or operational efficiency, moving into leadership roles, or transitioning into strategic planning functions, mirroring the development paths available in UX research.

🌐 Work Environment

Office Type: Modern, collaborative tech office environment.
Office Location(s): Primarily based in Google's London office, offering state-of-the-art facilities and a vibrant, innovative workspace.

Workspace Context:

Highly collaborative environment where interaction with colleagues from diverse disciplines is encouraged, fostering a rich exchange of ideas and perspectives.
Access to cutting-edge tools, technologies, and internal research platforms designed to support rigorous data analysis and user research.
Opportunities for informal and formal knowledge sharing sessions, brown bags, and cross-team discussions that enhance understanding of different operational and research methodologies.

Work Schedule:

The role is on-site, requiring regular presence in the London office to facilitate collaboration and team integration. While a standard 40-hour week is typical, the dynamic nature of product development may require flexibility to meet project deadlines.

📝 Enhancement Note: Similar to operations roles in tech, the work environment emphasizes collaboration, access to advanced tools, and a culture of continuous learning. On-site presence is often valued for team cohesion and spontaneous problem-solving, though hybrid models are also common.

📄 Application & Portfolio Review Process

Interview Process:

Initial Screening: A recruiter or hiring manager will review your application and resume, focusing on your quantitative research experience and alignment with the minimum qualifications.
Technical Interview(s): Expect interviews that delve into your quantitative research methodologies, statistical knowledge, programming skills (Python/R/SQL), and experience with various data analysis techniques. You may be asked to discuss past projects in detail.
Portfolio Review/Presentation: You will likely be asked to present a selection of your work, showcasing your ability to define research problems, execute studies, analyze data, and communicate findings effectively to a panel of researchers, designers, and product managers.
Cross-Functional Collaboration Interview: Assess your ability to work with designers, engineers, and product managers, and how you influence product decisions based on research.
Behavioral/Situational Interviews: Questions will assess your problem-solving skills, teamwork, communication, and how you handle challenges in a fast-paced environment.

Portfolio Review Tips:

Quantify Impact: For each project, clearly articulate the problem you addressed, your methodology, the key findings, and the tangible impact your research had on the product or business. Use metrics and data to support your claims.
Showcase Process: Demonstrate your systematic approach to research, from problem definition and hypothesis generation to data collection, analysis, and reporting. Explain your choices and rationale.
Highlight Collaboration: Include examples where you successfully collaborated with cross-functional teams, showing how you integrated diverse perspectives and influenced product decisions.
Tailor to Wear OS: If possible, draw parallels between your past work and the challenges or opportunities within the Wear OS ecosystem.

Challenge Preparation:

Be ready to discuss specific quantitative research projects in depth, including the challenges encountered and how you overcame them.
Prepare to explain complex statistical concepts and analytical techniques in a clear, understandable manner.
Practice presenting your work concisely and persuasively, focusing on the insights and impact.
Familiarize yourself with Google's product suite, particularly Wear OS, and consider potential user experience challenges and research questions.

📝 Enhancement Note: Operations candidates should prepare similar portfolio presentations, focusing on process improvements, data analysis projects demonstrating efficiency gains, and quantifiable business impact. Technical interviews will likely focus on CRM systems, sales analytics tools, and data modeling relevant to revenue generation.

🛠 Tools & Technology Stack

Primary Tools:

Statistical Programming Languages: Python (with libraries like Pandas, NumPy, SciPy, Scikit-learn), R (with libraries like dplyr, ggplot2, caret).
Database Querying: SQL for data extraction and manipulation from large databases.
Survey Platforms: Experience with tools like Qualtrics, SurveyMonkey, or Google Forms for survey design and deployment.
Data Visualization Tools: Tableau, Looker, D3.js, or similar tools for creating insightful dashboards and reports.

Analytics & Reporting:

Log Analysis: Experience with analyzing user interaction logs and event data.
Web Analytics Tools: Familiarity with platforms like Google Analytics or similar for tracking user behavior and performance.
Experimentation Tools: Understanding of A/B testing methodologies and platforms for controlled user studies.

CRM & Automation:

While not a direct CRM role, understanding how user data is collected and managed within product ecosystems is beneficial. Familiarity with data pipelines and integration tools may be advantageous.

📝 Enhancement Note: Operations professionals will find common ground in SQL, data visualization tools, and analytics platforms. CRM systems (like Salesforce) and sales automation tools (like HubSpot, Marketo) are central to operations tech stacks, along with business intelligence tools (like Power BI, Tableau) for reporting and analysis.

👥 Team Culture & Values

Operations Values:

User Focus: A deep commitment to understanding and advocating for the user, ensuring their needs and behaviors are central to product development.
Data-Driven: A reliance on empirical evidence and quantitative analysis to inform decisions and validate hypotheses, fostering objectivity and rigor.
Collaboration: A proactive approach to working with cross-functional teams, valuing diverse perspectives and collective problem-solving.
Impact: A drive to create meaningful improvements in user experience and product success, measured through concrete outcomes and metrics.
Innovation: A continuous pursuit of new methods and insights to enhance user understanding and product quality.

Collaboration Style:

Highly collaborative, with a strong emphasis on cross-functional partnerships. Researchers are expected to integrate seamlessly with design, engineering, and product management teams.
Open communication and feedback are encouraged, fostering a culture of continuous learning and improvement within the team.
Knowledge sharing through internal forums, presentations, and mentoring programs is common, promoting collective growth and expertise.

📝 Enhancement Note: Operations teams also highly value data-driven decision-making, efficiency, collaboration with sales and marketing, and a focus on measurable impact (e.g., revenue growth, pipeline efficiency, customer acquisition cost).

⚡ Challenges & Growth Opportunities

Challenges:

Balancing Rigor and Speed: Conducting deep, rigorous quantitative research while meeting the fast-paced demands of product development cycles.
Data Complexity: Working with vast and diverse datasets, requiring advanced skills in data cleaning, integration, and analysis to extract meaningful insights.
Influencing Product Decisions: Effectively communicating complex quantitative findings to diverse stakeholders and driving consensus for data-informed product changes.
Measuring Nuance: Quantifying qualitative aspects of user experience and translating subjective user feedback into measurable metrics.

Learning & Development Opportunities:

Advanced Analytics Training: Access to internal and external training on cutting-edge statistical methods, machine learning, and data science techniques applicable to UX research.
Industry Conferences: Opportunities to attend and present at leading UX research and data science conferences.
Mentorship Programs: Benefit from mentorship from senior researchers and leaders within Google's extensive UX community.
Cross-Disciplinary Learning: Learn from world-class designers, engineers, and product managers, broadening your understanding of the product development ecosystem.

📝 Enhancement Note: Operations professionals often face challenges related to data integrity, process bottlenecks, and aligning disparate departmental goals. Growth typically involves mastering new analytical tools, developing strategic planning skills, and taking on leadership responsibilities for operational efficiency and revenue growth initiatives.

💡 Interview Preparation

Strategy Questions:

"Describe a time you used quantitative data to identify a significant user problem and how you influenced the product team to address it." Focus on your research design, analysis, and communication of impact.
"How do you approach defining and measuring key quantitative UX metrics for a new feature or product?" Be prepared to discuss metric selection criteria and validation methods.
"Walk us through your process for designing and executing a large-scale survey study." Detail your methodology for sampling, questionnaire design, data analysis, and interpretation.

Company & Culture Questions:

"Why are you interested in working on Wear OS specifically?" Show genuine interest and understanding of the platform's user base and challenges.
"How do you handle situations where your research findings conflict with stakeholder opinions or existing product plans?" Emphasize your data-driven approach and communication skills.
"Describe your experience collaborating with designers and engineers. How do you ensure your research insights are effectively integrated into the design and development process?"

Portfolio Presentation Strategy:

Structure: Organize your portfolio around 2-3 key projects. For each, clearly state the objective, your role, the methodology, the key findings, and the impact.
Data Storytelling: Focus on telling a compelling story with your data. Visualize your key findings effectively and explain the "so what?" behind the numbers.
Quantify Impact: Whenever possible, use metrics to demonstrate the impact of your work (e.g., "Our research led to a 15% increase in feature adoption" or "Identified a usability issue affecting 20% of users").
Conciseness: Be mindful of time constraints. Practice your presentation to ensure it is clear, concise, and impactful.

📝 Enhancement Note: For operations interviews, prepare to discuss specific metrics you’ve tracked (e.g., conversion rates, sales cycle length, pipeline velocity), case studies of process improvements you’ve implemented, and how you’ve used data to drive revenue or efficiency. Be ready to articulate your understanding of the company's go-to-market strategy.

📌 Application Steps

To apply for this quantitative UX research position:

Submit your application through the Google Careers portal.
Resume Optimization: Tailor your resume to highlight your quantitative research experience, programming skills (Python, R, SQL), survey design expertise, and experience in influencing product decisions with data. Use keywords from the job description.
Portfolio Preparation: Curate a portfolio that showcases your strongest quantitative research projects, emphasizing data analysis, impact quantification, and collaborative achievements. Ensure it's easily accessible (e.g., PDF, personal website).
Interview Practice: Prepare to discuss your portfolio projects in detail, practice answering behavioral and situational questions, and brush up on your statistical knowledge and programming skills.
Company Research: Familiarize yourself with Google's mission, values, and specifically the Wear OS product. Understand its market position and user base.

⚠️ 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.

Senior Quantitative UX Researcher, Wear OS