Product Design Researcher
Job Description
Publicis Groupe Holdings B.V. sits at the crossroads of human behavior and product strategy in Irving, Texas, where this on-site role centers the design team on what users actually do. The Product Design Researcher owns the user research agenda, translating insights into actionable roadmaps and business outcomes that steer product decisions and design directions.
Responsibilities
- Own research studies end-to-end: define the question, select the right methodology, recruit participants, facilitate sessions, synthesize findings, and deliver a clear recommendation rather than a report.
- Evaluate each research challenge on its own terms and advocate confidently for the most appropriate method, whether it is contextual inquiry, diary study, moderated usability test, survey, card sort, or a combination based on what the question requires.
- Plan and moderate qualitative sessions (interviews, usability tests, inquiries) with warmth and confidence, making participants comfortable and eliciting honest, actionable responses.
- Design and analyze quantitative studies (surveys, tree tests, benchmarking, analytics review) and weave those results with qualitative insights to tell a complete story.
- Utilize research tools such as Looppanel and Lyssna to accelerate operations like transcription, affinity mapping, and initial pattern recognition, while applying human judgment to interpret meaning.
- Build and maintain a shared research repository, ensuring past findings are discoverable and usable by the broader product team in our MCP research system.
- Communicate findings to cross-functional partners, including product, engineering, and leadership, through structured presentations that connect user behavior to business outcomes and product decisions.
- Collaborate with Product Designers and Product Managers throughout the lifecycle, from generative discovery to evaluative testing of shipped features.
- Foster a user-centered culture by running research office hours, sharing findings broadly, and making it easier for non-researchers to engage meaningfully with user insights.
- Stay current with evolving research tools, AI-assisted workflows, and new methodologies, proactively surfacing approaches that could improve quality or efficiency.
Requirements
- Three to five years of hands-on UX research experience on digital products, with a portfolio that demonstrates studies you owned from question to recommendation.
- Fluency in both qualitative methods (in-depth interviews, usability testing, contextual inquiry, diary studies) and quantitative methods (surveys, card sorts, tree tests, product analytics review).
- A confident, energetic presence in the room, comfortable facilitating one-on-one sessions with enterprise users and presenting findings to senior stakeholders.
- The judgment to assess a research question and recommend the right method rather than default to the familiar approach.
- Practical experience using AI tools to accelerate synthesis and operational tasks, with a clear sense of where human interpretation must lead.
- Strong written and verbal communication skills, with the ability to distill complex findings into a decisive point of view.
- A working knowledge of how digital products are built and where research fits within agile, iterative product cycles.
- A degree in Human-Computer Interaction, Cognitive Science, Psychology, Anthropology, or a related behavioral discipline, or equivalent professional experience.
- An accessible portfolio or case studies showing not just the methods used, but the decisions those studies influenced.
Technologies
- Looppanel
- Lyssna
Why you might stand out
- You walk into a research brief with a point of view on the right approach, without waiting for others to define the methodology.
- You have presented findings to skeptical stakeholders and helped steer a product decision in a new direction.
- You bring a distinct facilitation style: genuine curiosity, quick rapport, and the ability to ask the follow-up questions that reveal the real answer.
- You view AI as a productivity layer, not a substitute for thinking, and you verify AI-generated synthesis with human checks.
- You have contributed to or helped establish a research repository that the wider team actually uses.
- You are comfortable navigating ambiguity and can define the research question when the brief is incomplete.
- You have experience collaborating with data analysts or data scientists to triangulate qualitative findings with behavioral or product analytics data.
- You understand the difference between methodologically sound research and research that meaningfully influences what gets built, and you optimize for the latter.