Survey Scientist, AI and Compute Enablement

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 4 years of experience in product research in an applied research setting, or similar.
• Experience in survey design and analysis (e.g., sampling, weighting surveys answers, writing questionnaires, pre-testing question wording, or longitudinal survey research program).

Preferred qualifications:

• Advanced degree in Human-Computer Interaction (HCI), Human Factors, Psychology, or a related field, or equivalent practical experience.
• Experience leveraging advanced research methods (e.g., psychometrics, sampling, segmentation, performance analysis) to successfully drive product improvements.
• Experience collaborating with multidisciplinary teams of Designers, Engineers, and Product Managers throughout the product development process.
• Experience in front-end development, technical UX design, or prototyping with the knowledge of AI/ML research/development.
• Ability to work on novel and technical solutions in a fast-changing space.
• Passionate for Generative AI systems and the developers who build them.

About the job

At Google, we follow a simple but vital premise: "Focus on the user and all else will follow." User Experience Researchers (UXRs) make this possible.

Google User Experience (UX) is made up of multi-disciplinary teams of UX Designers, Researchers, Writers, Content Strategists, Program Managers, and Engineers: we care deeply about the people who use our products. The UX team plays an integral part in gathering insights about the needs, attitudes, emotions, and behaviors of people who use our products to inspire and inform design. We collaborate closely with each other and with engineering and product management to create industry-leading products that deliver value for the people who use them, and for Google’s businesses.

As a User Experience Researcher (UXR), you’ll help your team of UXers, product managers, and engineers understand user needs. You’ll work with stakeholders across functions and levels and have impact at all stages of product development. You’ll play a critical role in creating useful, usable, and delightful products. You’ll explore user behaviors and motivations by conducting primary research such as field studies, interviews, diary studies, participatory workshops, ethnography, surveys, usability testing, and logs analysis.

The UXR community at Google is unique and will help you do your best work. You’ll have the opportunity to work with and learn from UXRs across Google through regular meetups, mentor programs, and access to internal research tools.

The AI and Compute Enablement (ACE) team, part of MSCA, drives Google's next-gen user-centric AI and compute innovations. We provide the platforms and infrastructure to easily build and deploy AI/ML into products for both internal and external customers.Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

Responsibilities

• Identify and prioritize high-impact research opportunities that strategically align with product, design, and business objectives, defining roadmaps for ML Systems and Cloud AI (MSCA) products and solutions.
• Scope and execute research using a wide variety of advanced techniques, including questionnaire design, psychometrics, sampling, and data weighting. Your work will identify and optimize factors influencing customer pain points and business success.
• Connect behavioral and survey data to extract meaningful patterns from large datasets and generate insights, reports, and presentations that inspire user-centricity, deliver business intelligence to cross-functional partners, and inform product decisions at scale.
• Build strong partnerships across the organization, integrating complex technical and business expertise into your research, and leveraging user data to effectively navigate ambiguity.